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. 2021 Oct;57(5):737-751.
doi: 10.1111/1752-1688.12917. Epub 2021 May 27.

Monitoring Turbidity in San Francisco Estuary and Sacramento-San Joaquin Delta Using Satellite Remote Sensing

Affiliations

Monitoring Turbidity in San Francisco Estuary and Sacramento-San Joaquin Delta Using Satellite Remote Sensing

Christine M Lee et al. J Am Water Resour Assoc. 2021 Oct.

Abstract

This study utilizes satellite data to investigate water quality conditions in the San Francisco Estuary and its upstream delta, the Sacramento-San Joaquin River Delta. To do this, this study derives turbidity from the European Space Agency satellite Sentinel-2 acquired from September 2015 to June 2019 and conducts a rigorous validation with in situ measurements of turbidity from optical sensors at continuous monitoring stations. This validation includes 965 matchup comparisons between satellite and in situ sensor data across 22 stations, yielding R 2 = 0.63 and 0.75 for Nephelometric Turbidity Unit and Formazin Nephelometric Unit (FNU) stations, respectively. This study then applies remote sensing to evaluate patterns in turbidity during the Suisun Marsh Salinity Control Gates Action ("Gates action"), a pilot study designed to increase habitat access and quality for the endangered Delta Smelt. The basic strategy was to direct more freshwater into Suisun Marsh, creating more low salinity habitat that would then have higher (and more suitable) turbidity than upstream river channels. For all seven acquisitions considered from June 29 to September 27, 2018, turbidity conditions in Bays and Sloughs subregions were consistently higher (and more suitable) (26-47 FNU) than what was observed in the upstream River region (13-25 FNU). This overall pattern was observed when comparing images acquired during similar tidal stages and heights.

Keywords: Delta Smelt; San Francisco Estuary; Suisun Marsh; remote sensing; turbidity; water quality.

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Figures

FIGURE 1
FIGURE 1
Study area for San Francisco Estuary and Sacramento–San Joaquin Delta, including locations of 22 CDEC fixed water quality stations, and subregions used to evaluate the Suisun Marsh Salinity Control Gates Action. Black boxes correspond with locations of 11 CDEC stations reporting in Formazin Nephelometric Unit [FNU]; grey boxes correspond with 11 CDEC stations reporting in Nephelometric Turbidity Unit [NTU].
FIGURE 2
FIGURE 2
Comparing Sentinel‐2 derived turbidity with CDEC station reported turbidity. (a) depicts S2 vs. CDEC (NTU) and (b) depicts S2 vs. CDEC (FNU). Vertical error bars reflect standard deviation over spatial domain (3 × 3 pixels from Sentinel‐2). Note that many of the vertical error bars are smaller than the plot marker for Sentinel‐2 turbidity values. Solid line represents the regression line and the dotted lines represent the 1:1 line.
FIGURE 3
FIGURE 3
Boxplots of Sentinel‐2 turbidity values by subregion.
FIGURE 4
FIGURE 4
Sentinel‐2 turbidity maps acquired prior to, during, and after the Gates action over subregions corresponding with Figure 1. (a) June 29, 2018; (b) July 14, 2018; (d) July24, 2018; (e) August 13, 2018; (f) September 2, 2018; (g) September 27, 2018. Two images (e,f) were acquired during the Gates action. Black areas within the subregions (Figure 1) correspond with portions of the image masked due to cloud cover. Black areas within the image (outside of the subregions) are outside of the boundary of interest.
FIGURE 5
FIGURE 5
Time series plots of spatial averages of turbidity by subregion. Red bars denote period of Gates operation. Black columns denote conditions during the same tidal stage. Grey columns show conditions during other tidal stages.
FIGURE 6
FIGURE 6
Bay Delta Live (https://nasa.baydeltalive.com) provides access to NASA Earth science data, in‐situ monitoring stations, special studies in comprehensive dashboard format including maps, data visualization, map stories and collaborative workspaces.
FIGURE 7
FIGURE 7
Interactive dashboard to visualize the results of the automated Sentinel‐2 turbidity pipeline. Users can select which water quality parameter and remote sensing algorithm to display. Results are plotted on an interactive graph with correlation coefficients, standard deviation metrics, and best fit lines. Station data is also plotted spatial and available on the map interface.

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