The coastal water quality of Mumbai is deteriorating due to various point and non-point wastewater sources. Hence, it is desirable to monitor coastal water quality for various water-related activities like bathing, contact water sports, recreation, and commercial fishing. The objective of this paper is to assess the seasonal water quality on the basis of seawater standards. Based on water-quality analysis of 17 seafronts and beaches, most of the parameters were exceeding the standards. The statistical cluster analysis was carried out for evaluating impact of wastewater and sewage discharges. The hierarchical cluster analysis resulted into three clustered groups, namely less polluted, moderately polluted, and highly polluted sites with similar characteristics of water quality. Mahim was found to be worst-affected beach due to incoming organic load from the Mithi river in comparison to other seafronts and beaches. Unaccounted sources of sewage and wastewater should be identified and rerouted through sewerage system by improving collection efficiency, treatment, and proper disposal for achieving designated receiving water quality standards.

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Geospatial approaches to monitoring and mapping water quality over a wide range of temporal and spatial scales have the potential to save field and laboratory efforts. The present study depicts the estimation of water quality parameters, namely turbidity and phosphate, through regression analysis using the reflectance derived from remote sensing data on the west coast of Mumbai, India. The predetermined coastal water samples were collected using the global positioning system (GPS) and were measured concurrently with satellite imagery acquisition. To study the influence of wastewater, the linear correlations were established between water quality parameters and reflectance of visible bands for either set of imagery for the study area, which was divided into three zones: creek water, shore‐line water and coastal water. Turbidity and phosphate have the correlation coefficients in the range 0.75–0.94 and 0.78–0.98, respectively, for the study area. Negative correlation was observed for creek water owing to high organic content caused by the discharges of domestic wastewater from treatment facilities and non‐point sources. Based on the least square method, equations are formulated to estimate turbidity and phosphate, to map the spatial variation on the GIS platform from simulated points. The applicability of satellite imagery for water quality pattern on the coast is verified for efficient planning and management.

The water quality of seafronts and beaches of Mumbai is under pressure and deteriorating due to discharge of partially treated sewage and wastewater through point and nonpoint sources. The objective of the study was to assess the water quality and to correlate physico-chemical and bacteriological parameters for establishing relationship, association and dependence on each other. The water quality parameters were selected as per SW II standards specified by Central Pollution Control Board, India and nutrient parameters as strong indicators of sewage pollution. Box and whisker plots were generated for evaluating spatio temporal variation of water quality which suggest influence of organic pollution mostly at Mahim and Dadar in the form of outliers and extremes. Pearson's correlations were estimated between parameters and found significant correlation with each other indicating influence of sewage on water quality. The water quality of beaches and seafronts were found unsafe for recreational purposes. The study suggested that designated water quality can be achieved by restricting nonpoint source through improvement in wastewater collection systems, appropriate level of treatment and proper disposal.