Assessment of coastal water quality along south west coast of India using multile regression analysis on satellite data

Abstract

The coastal waters being the ultimate receiver of all the wastes, shows a declining trend in its quality. It is of immense importance to know the extent of pollution for its monitoringandmanagemenlMeasurementofdissolvedoxygen (DO), biologicaloxygen demand (BOD), pH and fecal coliform (FC) are vital in water quality monitoring and assessment studies. Usually these parameters are determined by analysing water samples collected from various locations. Since this is tedious and expensive, it is limited to small scales. In this paper, an effort has been made to quickly assess the quality of coastal waters of Kerala directly from the satellite imagery by estimating National Sanitation Federation Water Quality Index (NSFWQI) along with DO, BOD, pH and FC. Multiple linear regression is used to develop statistically significant models using Sea Surface Temperature (SST) and Remote Sensing Reflectance (R<inf>rs</inf>) from Moderate Resolution Imaging Spectroradiometer (MODIS) and in-situ data available on DO, BOD, pH and FC. The models when validated showed good correlation between in situ values and predicted values with r values ranging from 0.73 (p=0.001) for DO to 0.89 for NSFWQI (p=0.018). Spatial maps are generated showing the distribution of these parameters along the coast. The parameters in the study are checked to see if they are in compliance with the standards. The study gives models to estimate the daily distribution of these parameters along the coast using MODIS data. Thus, appropriate control measures could be adopted to limit the effect on susceptible rural population. © 2019 JPR Solutions. All rights reserved.