Optical Properties Of Coastal Waters Research Articles

Monitoring multi-temporal and spatial variations of water transparency in the Jiaozhou Bay using GOCI data

Water transparency, commonly measured as Secchi disk depth (SDD), is essential for describing the optical properties of coastal waters. We proposed a regional linear corrected SDD estimation model based on the North Sea Mathematical Models for GOCI and the mechanical model developed by Lee et al. (2015) in the Jiaozhou Bay. Combined with the multiple variable linear regression analysis, the diurnal SDD variations of the bay inside and the bay mouth are controlled by the solar zenith angle (SZA) and tides. The bay outside mainly varies with SZA. From GOCI observations between 2011 and 2021, wind force influenced the entire area on the inner-annual SDD variations. It exhibits an increasing trend in the inter-annual dynamics, which was more stable inside the bay with an annual increase of 0.035 m, and air temperature was the most significant contribution. However, human activities cannot be ignored in causing water environment changes.

Evaluation of Empirical and Machine Learning Algorithms for Estimation of Coastal Water Quality Parameters

Coastal waters are one of the most vulnerable resources that require effective monitoring programs. One of the key factors for effective coastal monitoring is the use of remote sensing technologies that significantly capture the spatiotemporal variability of coastal waters. Optical properties of coastal waters are strongly linked to components, such as colored dissolved organic matter (CDOM), chlorophyll-a (Chl-a), and suspended solids (SS) concentrations, which are essential for the survival of a coastal ecosystem and usually independent of each other. Thus, developing effective remote sensing models to estimate these important water components based on optical properties of coastal waters is mandatory for a successful coastal monitoring program. This study attempted to evaluate the performance of empirical predictive models (EPM) and neural networks (NN)-based algorithms to estimate Chl-a and SS concentrations, in the coastal area of Hong Kong. Remotely-sensed data over a 13-year period was used to develop regional and local models to estimate Chl-a and SS over the entire Hong Kong waters and for each water class within the study area, respectively. The accuracy of regional models derived from EPM and NN in estimating Chl-a and SS was 83%, 93%, 78%, and 97%, respectively, whereas the accuracy of local models in estimating Chl-a and SS ranged from 60–94% and 81–94%, respectively. Both the regional and local NN models exhibited a higher performance than those models derived from empirical analysis. Thus, this study suggests using machine learning methods (i.e., NN) for the more accurate and efficient routine monitoring of coastal water quality parameters (i.e., Chl-a and SS concentrations) over the complex coastal area of Hong Kong and other similar coastal environments.

Inputs of humic fluorescent dissolved organic matter via submarine groundwater discharge to coastal waters off a volcanic island (Jeju, Korea)

The abundance of fluorescent dissolved organic matter (FDOM) in the surface ocean plays a critical role in the growth of marine microorganisms and corals by affecting the optical properties (i.e., the penetration of UV radiation) of seawater. In general, it is known that rivers are the main source of FDOM to surface ocean waters. Here, however, we show that the concentrations of FDOM in coastal seawater off a volcanic island, Jeju, Korea, are dependent primarily on submarine groundwater discharge (SGD). Based on a significant correlation between 222Rn and salinity in seawater, fresh groundwater was found to be the main source of groundwater as well as fresh water in the bay. The addition of dissolved organic carbon (DOC) and protein-like FDOM to the bay via SGD was generally negligible or negative. However, SGD enhanced the inventory of humic-like FDOM (FDOMH) in seawater by 2–3 times over all seasons, with conservative behavior of FDOMH in bay seawater. These results suggest that SGD-driven fluxes of FDOM regulate its inventory in seawater and consequently play a significant role in determining the optical properties of coastal waters off islands and associated coastal ecosystems (i.e., corals).

Spatial scales of optical variability in the coastal ocean: Implications for remote sensing and in situ sampling

AbstractUse of ocean color remote sensing to understand the effects of environmental changes and anthropogenic activities on estuarine and coastal waters requires the capability to measure and track optically detectable complex biogeochemical processes. An important remote sensor design consideration is the minimum spatial resolution required to resolve key ocean features of physical and biological significance. The spatial scale of variability in optical properties of coastal waters has been investigated using continuous, along‐track measurements collected using instruments deployed from ships, aircraft, and satellites. We defined the average coefficient of variance, , within an image pixel as the primary statistical measure of subpixel variability and investigated how changes as a function of the Ground Sampling Distance (GSD). In general, d /dGSD is positive, indicating that the subpixel variability increases with GSD. The relationship between and GSD is generally nonlinear and the greatest rate of change occurs at small spatial scales. Points of distinct transition in the relationship between and GSD are evident between 75 and 600 m, varying depending on the location and the optical parameter, and representing the GSD above which most of the spatial variability due to small‐scale features is subsumed within a pixel. At GSDs greater than the transition point, most of the small‐scale variability occurs at subpixel scales and, therefore, cannot be resolved. On average, the transition GSD is around 200 m. The results have application in both sensor design and in situ sampling strategy in support of coastal remote sensing operations.

Optical variability along a river plume gradient: Implications for management and remote sensing

Effective assessment and management of seagrass distributions require a thorough understanding of the water environment, in particular the inherent optical properties (IOPs) of the water column, and the linkage with environmental forcing such as coastal run-off. Coastal waters off the Suwannee and Steinhatchee rivers in the northeastern Gulf of Mexico where seagrass is abundant were sampled regularly in 2010 and 2011 during periods ranging from normal spring flooding to record-low flow conditions associated with widespread drought. Relationships between surface salinities, chlorophyll a concentrations (Chl-a), and IOPs were examined to characterize the optical variability of this region as well as its connection with river discharge and wind forcing. Significant spatial and temporal variability was observed for Chl-a (0.285–14.4mgm−3), colored dissolved organic matter (CDOM) absorption at 443nm, aCDOM(443), (0.042–7.53m−1), and particulate backscattering at 660nm, bbp(660), (0.002–0.067m−1) with gradients evident between nearshore (riverine) and offshore (oceanic) waters. Overall, CDOM was the dominant optically significant constituent (OSC), contributing ∼74–75±11% to total (non-water) absorption at 443nm and 555nm. CDOM was mainly controlled by river flow, with an inverse correlation observed between aCDOM(443) and salinity (r2=0.66). Chl-a showed less direct dependence on flow, exhibiting elevated concentrations (>5mgm−3) mainly during the summer. Particulate backscattering in this region was relatively low and largely controlled by non-algal particles, as was evident by the strong relationship between bbp(660) and detrital absorption at 443nm, ad(443) (r2=0.71). Compared with other coastal waters in the eastern Gulf of Mexico, aCDOM(443) was ∼3–5 times higher and bbp(660) was ∼50% lower, making the study region very dark. Given that the optical properties of coastal waters in this region are strongly influenced by CDOM derived from terrestrial discharge, remote-sensing algorithms for determining long-term Chl-a trends should focus on utilizing wavebands less influenced by CDOM.

Deriving optical properties of Mahakam Delta coastal waters, Indonesia using in situ measurements and ocean color model inversion

The development of an operational water quality monitoring method based on remote sensing data requires information on the apparent and inherent optical properties of water (AOP and IOP respectively). This study was performed to determine the apparent and inherent optical properties of coastal waters of the Mahakam Delta, Kalimantan, Indonesia. Inherent optical properties (IOPs) were derived from above-water radiometric measurements and ocean color model inversion. Retrieved IOPs and measured concentrations show good agreement both for total suspended matter (TSM) and chlorophyll a (Chl a) (R2=0.72 and 0.80 respectively). The linear relationship between the retrieved IOPs and the measured concentrations was then used to estimate the specific inherent optical properties (SIOPs) using the basic equation of the Lambert–Beer law. The specific backscattering coefficient of TSM (bb,TSM∗(550)) was found to be 0.0087m2g−1, and the specific absorption coefficient of Chl a (aChl∗(440)) was found to be 0.023m2g−1 in the Mahakam Delta. The estimated values of SIOP for TSM and Chl a could be considered spatially constant for the Mahakam Delta, and resulted in reliable estimates of TSM and Chl a concentrations (R2=0.84 and 0.85 respectively). The specific backscattering coefficient of TSM found in this study is similar to that of the Barito Estuary (in the southern part of Kalimantan) but lower than that of the Berau Estuary (in the northern part of Kalimantan), whereas the specific backscattering coefficient of Chl a is similar to that found in the Berau Estuary. This study contributes to the development of an operational method based on remote sensing data to map water constituent concentrations in the Mahakam Delta, as well as to enrich the information about the optical properties of Indonesian waters.

Mapping coloured dissolved organic matter concentration in coastal waters

Optical properties of the Baltic Sea are dominated by coloured dissolved organic matter (CDOM). High concentration of CDOM is probably one of the reasons why standard chlorophyll-retrieval algorithms fail badly in the Baltic Sea. Our aim was to test can CDOM be mapped by remote sensing instruments in coastal waters of relatively CDOM-rich environments like the Baltic Sea. The results show that sensors with high radiometric resolution, such as Advanced Land Imager (ALI), can be used for mapping CDOM in a wide concentration range. The ALI image also showed that optical properties of coastal waters are extremely variable. CDOM concentration may vary 4–5-fold in two adjacent 30 m pixels. This indicates a need for relatively high spatial resolution (30 m or less) remote sensing data in monitoring coastal environments.

Characteristics and potential impacts of under-ice river plumes in the seasonally ice-covered Bothnian Bay (Baltic Sea)

The northernmost basin of the Baltic Sea, the Bothnian Bay, is ice-covered for about half the year. During this time, distinct under-ice river plumes develop, even seaward of the smallest rivers, that are substantially thicker and larger in extent than during the summer months. Wind mixing is negligible, and during late spring in April or May, the highest annual discharge occur while the sea is ice covered, thus providing conditions for the formation of extensive under-ice plumes. These plumes are characterised by high levels of trace elements (e.g., Al, Fe and Zn), organic matter (TOC and dissolved organic carbon [DOC]), nutrients and also optically active substances (colored dissolved organic matter, CDOM). The under-ice plumes provide an important pathway for undiluted transport of land-derived substances to the pelagic waters of the basin, affecting the salinity, chemistry and optical properties of coastal waters. Freshwater ice growth on the underside of an existing sea ice sheet also restricts the buildup of sea ice and under-ice algal communities, potentially in large areas along the coasts. Plume water influences the optical characteristics of coastal waters for a period of time after ice break-up, potentially affecting primary production in these areas. Furthermore, the formation of under-ice plumes potentially has a positive feedback on the ice season length due to freshening of the coastal waters (earlier freeze-up) and restricted oceanic heat flux (slower melting).