Spatial Variability of Suspended Sediments in San Francisco Bay, California

Abstract

Understanding spatial variability of water quality in estuary systems is important for making monitoring decisions and designing sampling strategies. In San Francisco Bay, the largest estuary system on the west coast of North America, tracking the concentration of suspended materials in water is largely limited to point measurements with the assumption that each point is representative of its surrounding area. Strategies using remote sensing can expand monitoring efforts and provide a more complete view of spatial patterns and variability. In this study, we (1) quantify spatial variability in suspended particulate matter (SPM) concentrations at different spatial scales to contextualize current in-water point sampling and (2) demonstrate the potential of satellite and shipboard remote sensing to supplement current monitoring methods in San Francisco Bay. We collected radiometric data from the bow of a research vessel on three dates in 2019 corresponding to satellite overpasses by Sentinel-2, and used established algorithms to retrieve SPM concentrations. These more spatially comprehensive data identified features that are not picked up by current point sampling. This prompted us to examine how much variability exists at spatial scales between 20 m and 10 km in San Francisco Bay using 10 m resolution Sentinel-2 imagery. We found 23–80% variability in SPM at the 5 km scale (the scale at which point sampling occurs), demonstrating the risk in assuming limited point sampling is representative of a 5 km area. In addition, current monitoring takes place along a transect within the Bay’s main shipping channel, which we show underestimates the spatial variance of the full bay. Our results suggest that spatial structure and spatial variability in the Bay change seasonally based on freshwater inflow to the Bay, tidal state, and wind speed. We recommend monitoring programs take this into account when designing sampling strategies, and that end-users account for the inherent spatial uncertainty associated with the resolution at which data are collected. This analysis also highlights the applicability of remotely sensed data to augment traditional sampling strategies. In sum, this study presents ways to supplement water quality monitoring using remote sensing, and uses satellite imagery to make recommendations for future sampling strategies.

Spatial Variability of In Situ Above-Water Reflectance in Coastal Dynamic Waters: Implications for Satellite Match-Up Analysis

“…However, according to the authors, depending on the local spatial scale of the bio-optical and optical constituents, the more pronounced changes in CV Δ happened for PGR lower than 100 m (coastal waters) and 200 m (offshore waters); still, the largest CV Δ were reported for pixel resolution higher than 400 m. Here, we did not investigate the R rs (0+) variability for PGR lower than 300 m since no current ocean color satellite presents finer resolution. The CV Δ depends on the spatial scale of the ocean dynamics and the optical constituents' concentration in the different waters (e.g., Moses et al, 2016;Taylor and Kudela, 2021). Here, we show the within-transect R rs (0+) variability (CV Δ ) along with the corresponding variability in turbidity, CDOM, Chl-a, and salinity acquired concurrently on 2 September 2019, as an example of our dataset (Figure 10).…”

Expanded Signal to Noise Ratio Estimates for Validating Next-Generation Satellite Sensors in Oceanic, Coastal, and Inland Waters

“…Second, quality-controlled data are available (see references in Section 2), and the sites are characterized well enough to assess their use as case studies for coastal and inland ocean color remote sensing. Third, the sites are both spatially extensive and optically homogenous for applying geostatistical methods to calculate the SNR [21,25,26]. Finally, datasets were excluded that were redundant with the previous analysis [21].…”

“…Data from C-AIR were obtained as part of the NASA Coastal High Acquisition Rate Radiometers for Innovative Environmental Research (C-HARRIER) campaign in collaboration with the NASA Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) experiment for offshore coastal waters, Monterey Bay, and Elkhorn Slough, California. Data from San Francisco Bay collected with the HydroRad-3 were obtained from a previous analysis [25] focusing on the derivation of Total Suspended Solids (TSS). HyperSAS data were collected in the Gulf of Mexico [28] and were obtained from the NASA SeaBASS repository [29].…”

“…The HydroRad-3 was deployed on the R/V Peterson in San Francisco Bay [25]. The HydroRad-3 recorded continuous radiometric measurements of E s , L i , and L T .…”

Spatial Patterns of Turbidity in Cartagena Bay, Colombia, Using Sentinel-2 Imagery

“…However, due to the significant spatial variability, mainly in coastal waters, higher spatial resolution remote sensing sensors such as the Landsat Family, i.e., Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+), and particularly the Operational Land Image (OLI) temporal series have been recently used to track water quality changes [21][22][23][24][25][26]. Since 2015, multispectral instruments (MSIs) on board the Sentinel-2 satellites have significantly improved spatial and temporal capabilities to study the behavior of biogeochemical parameters in several bays, including San Francisco Bay [27], Kastela Bay [28], the Bengal Bay [29], and Zhanjiang Bay [30]. The high spatial resolution of Sentinel-2 data makes them a valuable complement to traditional sampling strategies.…”