Application of Landsat 8 for monitoring impacts of wastewater discharge on coastal water quality
Trinh, Rebecca C.
Fichot, Cédric G.
Gierach, Michelle M.
Malakar, Nabin K.
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CitationRebecca C. Trinh, Cédric G. Fichot, Michelle M. Gierach, Benjamin Holt, Nabin K. Malakar, Glynn Hulley, Jayme Smith. 2017. "Application of Landsat 8 for Monitoring Impacts of Wastewater Discharge on Coastal Water Quality." Frontiers in Marine Science, Volume 4,
In this study, we examine the capabilities of the Landsat 8 Operational Land Imager (OLI), Thermal Infrared Sensor (TIRS), and Aqua Moderate resolution Imaging Spectroradiometer (MODIS) for monitoring the environmental impact of the 2015 Hyperion Treatment Plant (HTP) wastewater diversion in Santa Monica Bay, California. From 21 September−2 November 2015, the HTP discharged ~39 × 103 m3 h−1 of treated wastewater into Santa Monica Bay through their emergency 1-mile outfall pipe. Multi-sensor satellite remote sensing was employed to determine the biophysical impact of discharged wastewater in the shallow nearshore environment. Landsat 8 TIRS observed decreased sea surface temperatures (SST) associated with the surfacing wastewater plume. Chlorophyll-a (chl-a) concentrations derived from Landsat 8 OLI and Aqua MODIS satellite sensors were used to monitor the biological response to the addition of nutrient-rich wastewater. In situ chl-a and in situ remote sensing reflectance (Rrs) were measured before, during, and after the diversion event. These in situ data were paired with coincident OLI and MODIS satellite data to yield a more comprehensive view of the changing conditions in Santa Monica Bay due to the wastewater diversion. Two new local chl-a algorithms were empirically derived using in situ data for the OLI and MODIS sensors. These new local chl-a algorithms proved more accurate at measuring chl-a changes in Santa Monica Bay compared to the standard open ocean OC2 and OC3M algorithms, and the regional southern California CALFIT algorithm, as validated by in situ chl-a measurements. Additionally, the local OLI algorithm outperformed the local MODIS algorithm, especially in the nearshore region. A time series of chl-a, as detected by the local OLI chl-a algorithm, illustrated a very large increase in chl-a concentrations during the wastewater diversion, and a subsequent decrease in chl-a after the diversion. Our study demonstrates the capability of using Landsat 8 TIRS and OLI sensors for the monitoring of SST and surface chl-a concentrations at high spatial resolution in nearshore waters and highlights the value of these sensors for assessing the environmental effects of wastewater discharge in a coastal environment.