The Wastewater Contamination Index: A methodology to assess the risk of wastewater contamination from satellite-derived water quality indicators
de Liz Arcari, A.; Tavora, J.; van der Wal, D.; Salama, M.S. (2023). The Wastewater Contamination Index: A methodology to assess the risk of wastewater contamination from satellite-derived water quality indicators. Frontiers in Environmental Science 11: 1130655. https://dx.doi.org/10.3389/fenvs.2023.1130655 In: Frontiers in Environmental Science. Frontiers Media S.A.: Switzerland. e-ISSN 2296-665X, more |   |
| Author keywords | wastewater; contamination risk; optical remote sensing; water quality indicators; temporal anomalies |
| Authors | | Top | - de Liz Arcari, A.
- Tavora, J.
- van der Wal, D., more
- Salama, M.S.
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| Abstract | One of the major sources of pollution affecting inland and coastal waters is related to poorly treated or untreated wastewater discharge, particularly in urbanized watersheds. The excess of nutrients, organic matter, and pathogens causes an overall deterioration of water quality and impairs valuable ecosystem services. The detection of wastewater pollution is essential for the sustainable management of inland and coastal waters, and remote sensing has the capability of monitoring wastewater contamination at extended spatial scales and repeated frequencies. This study employed satellite-derived water quality indicators and spatiotemporal analysis to assess the risk of wastewater contamination in Conceição Lagoon, a coastal lagoon in Southern Brazil. Using an analytical model, three water quality indicators were derived from Level 2A Sentinel-2 MSI images: the absorption coefficients of chlorophyll-a and detritus combined with coloured dissolved organic matter, and the backscattering coefficient of suspended solids. The temporal standardized anomalies were calculated for each water quality indicator for the period of 2019–2021, and their anomalies during a known outfall event were used to evaluate spatial variation modes. The spatial mode explaining most of the variability was used to estimate weights for the water quality indicators anomalies in a linear transformation that can indicate the risk of wastewater contamination. Results showed that the wastewater spatial mode for this region was characterized by positive anomalies of backscattering coefficient of particulate matter and absorption coefficient of detritus combined with coloured dissolved organic matter, each with a relative importance of 50%. The application of this spatiotemporal analysis was formulated as the Wastewater Contamination Index. With the aid of photographic records, and additional meteorological and water quality data, the results of the index were verified for wastewater outfall events in the study area. The methodology for constructing the proposed Wastewater Contamination Index applies to other locations and can be a valuable tool for operational monitoring of wastewater contamination. |
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