Uncertainties and applications of satellite-derived coastal water quality products

Zheng, Guangming; DiGiacomo, Paul M.

doi:10.1016/j.pocean.2017.08.007

Cited by 84 publications

(56 citation statements)

References 265 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These constraints led to biases in satellite-derived water quality products [2], and may have limited our ability to resolve water quality in this study. Further, Zheng et al [47] reviewed satellite-derived ocean color products and concluded that, while coastal turbidity proxies tend to be relatively accurate in the 2-7 NTU range, they also tend to lose sensitivity beyond 7 NTU depending largely on colored dissolved organic matter concentration and atmospheric correction techniques. This relatively narrow range of turbidity values that tend to be accurately identified by satellite data may explain the paucity of significant relationships and prevalence of low R 2 adj values for many of these analyses, especially regarding extreme events (i.e., high-turbidity observations).…”

Section: Discussionmentioning

confidence: 99%

Water Quality Drivers in 11 Gulf of Mexico Estuaries

et al. 2018

View full text Add to dashboard Cite

Abstract:Coastal water-quality is both a primary driver and also a consequence of coastal ecosystem health. Turbidity, a measure of dissolved and particulate water-quality matter, is a proxy for water quality, and varies on daily to interannual periods. Turbidity is influenced by a variety of factors, including algal particles, colored dissolved organic matter, and suspended sediments. Identifying which factors drive trends and extreme events in turbidity in an estuary helps environmental managers and decision makers plan for and mitigate against water-quality issues. Efforts to do so on large spatial scales have been hampered due to limitations of turbidity data, including coarse and irregular temporal resolution and poor spatial coverage. We addressed these issues by deriving a proxy for turbidity using ocean color satellite products for 11 Gulf of Mexico estuaries from 2000 to 2014 on weekly, monthly, seasonal, and annual time-steps. Drivers were identified using Akaike's Information Criterion and multiple regressions to model turbidity against precipitation, wind speed, U and V wind vectors, river discharge, water level, and El Nino Southern Oscillation and North Atlantic Oscillation climate indices. Turbidity variability was best explained by wind speed across estuaries for both time-series and extreme turbidity events, although more dynamic patterns were found between estuaries over various time steps.

show abstract

Section: Discussionmentioning

confidence: 99%

Water Quality Drivers in 11 Gulf of Mexico Estuaries

et al. 2018

View full text Add to dashboard Cite

show abstract

“…One source is instrument calibration errors from satellite sensors, such as low signal‐to‐noise ratio. Uncertainties of

R_{r s}

mainly come from the ACs, including absorbing aerosols in coastal waters, but also from bed reflectance in shallow regions, adjacency effects, sun and sky glint, and underwater bubbles (Zheng & DiGiacomo, ). In addition,

ρ_{w}

in the red band saturates in highly turbid waters, and saturation is related to specific inherent optical properties of the suspended particles (Luo et al, ; Vanhellemont & Ruddick, ).…”

Section: Discussionmentioning

confidence: 99%

“…An accurate AC scheme is important for reliable applications of satellite remote sensing in coastal and estuarine areas. In those areas, applications of satellite ocean color data may be affected by sun glint, surface wave effects (Cox & Munk, 1954;Harmel et al, 2018), and adjacency effects, such as contributions from the surrounding land, ice, cloud, and object shadows (Bulgarelli & Zibordi, 2018;Zheng & DiGiacomo, 2017). The top-of-the-atmosphere radiance recorded by the satellite radiometer is separated into the signal from the atmospheric gases, aerosols, and the surface water column (Novoa et al, 2017).…”

Section: Landsat-8 Satellite Imagerymentioning

confidence: 99%

“…Another important issue regarding ocean color in coastal and estuarine areas is atmospheric correction (AC), the goal of which is to remove the effects of scattering by aerosols, which can be different over land and over water. In addition to the AC in coastal zones, the effects of surface wave glint and adjacency of surfaces of differing reflectance (i.e., land and water) also complicate the retrieval of ocean color in coastal zones (Bulgarelli & Zibordi, ; Zheng & DiGiacomo, ). With appropriate AC methods, various empirical algorithms have been derived for the retrieval of water constituents (e.g., SPM, chlorophyll‐a concentration) based on field data and remote sensing reflectance (

R_{r s}

) or reflectance band ratios in coastal regions (Doxaran et al, , ; Hu et al, ; Miller & McKee, ).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Correlation of Remotely Sensed Surface Reflectance With Forcing Variables in Six Different Estuaries

Tao

Hill

2019

JGR Oceans

View full text Add to dashboard Cite

This study examines the links between estuarine dynamics and longitudinal distributions of remotely sensed reflectance in estuaries. Reflectance at 655 nm from Landsat-8 correlates with in situ measurements of surface turbidity. Images collected from 2013 to 2018 are used to investigate the spatial and temporal characteristics of reflectance distribution in six selected estuaries with different dynamics. The results show that the maximum magnitude (C max ) and location (X max ) of the reflectance are functions of two major forcing variables, the freshwater discharge and tidal stage. Salt wedge estuaries (i.e., the Fraser River, Connecticut River, and Columbia River estuary) are affected strongly by river discharge and are relatively less affected by tidal forcing. In salt wedge estuaries, the C max values along the river channel are correlated with river discharge, while the X max values generally are not. In partially mixed to strain-induced periodic stratification (SIPS) estuaries (i.e., Delaware River) and SIPS-to-well-mixed estuaries (i.e., Gironde estuary), the X max values are correlated with river discharge, but the C max values are not. SIPS-to-well-mixed estuaries (i.e., Gironde estuary) and highly time-dependent salt wedge to well-mixed estuaries (i.e., Merrimack River estuary) are affected by tidal forcing. In these estuaries, the C max values are correlated with tidal stage. The C max values tend to be lower around high tide than low tide. Overall, the results demonstrate that remote sensing observations of ocean color can be utilized to infer subsurface estuarine processes. Satellite ocean color is a potential tool to monitor river discharge and to classify estuaries. Plain Language SummaryEstuaries are dynamic environments where river freshwater mixes with seawater. The relative strength of river flow relative to flow caused by ocean tides determines how and where freshwater and seawater mix in estuaries, which in turn affects various processes important to humans, like biological productivity and diversity, harbor siltation, and transport of pollutants. It is a challenge to classify estuaries on a global scale due to limited in situ observations. However, satellite remote sensing observations are able to provide repeated, snapshot views of surface water color over large spatial scale. In this study, we examine the links between estuarine dynamics and remote sensing observations in six different estuaries using satellite imagery. The observations demonstrate that satellite-derived maximum magnitude and position in surface reflectance, which is related to particle concentration, are correlated with river flow and tidal forcing, which can be used to infer different types of estuaries. Remotely sensed observations can also be useful for inferring the subsurface water mixing and sediment resuspension in estuaries. In addition, the responses of maximum in surface particle concentration and its location to river discharge can be used for satellite-based estimation of river discharge.

show abstract

“…In coastal waters, several studies have shown considerable potential for the application of EO-based methods for deriving water quality estimates (see reviews by Gholizadeh et al (2016) and Odermatt et al (2012)) over long temporal and spatial scales (i.e., regional, continental, and, ultimately, global), but the reliable application of these methods across time and space is complicated by the diversity of water types, sensor configuration, and inherent limitations of the approaches used (e.g., atmospheric effects, adjacency effect, sun glint, sea bottom reflectance, empirical algorithm restrictions) (Brewin et al 2015;Mouw et al 2015;Zheng and DiGiacomo 2017). In addition, water quality retrieval in optically complex coastal waters is often determined by a combination of spatially and temporally variable properties, such as phytoplankton, suspended material, and coloured dissolved organic matter, all of which affect water colour and transparency to varying degrees.…”

Section: Application 1 Optical Water Types For Coastal Water Qualitymentioning

confidence: 99%

Earth observation applications for coastal sustainability: potential and challenges for implementation

Politi¹,

Paterson

Scarrott

et al. 2019

Anthropocene Coasts

View full text Add to dashboard Cite

The coast is home to unique ecosystems, where complex ecological processes take place through the interaction of terrestrial, aquatic, atmospheric, and human landscapes. However, there are considerable knowledge and data gaps in achieving effective and future change-proof sustainable management of coastal zones around the world due to both technical and social barriers, as well as governance challenges. Currently, the role of Earth observation (EO) in addressing many of the recognised information gaps is small and under-utilised. While EO can provide much of the spatiotemporal information required for historical analysis and current status mapping, and offers the advantage of global coverage; its uptake can be limited by technical and methodological challenges associated mostly with lack of capacity and infrastructure, product accuracy and accessibility, costs, and institutional acceptance. While new initiatives and recent technological progress in the EO and information technology arena aim to tackle some of these issues so that EO products can be more easily used by non-EO experts, uptake is still limited. This paper discusses how EO can potentially inform transformative practices of planning in the coastal water zone, by using examples to demonstrate the EO potential in providing information relevant to decision-making framed by international agreements, such as the United Nations Agenda 2030, the Convention on Biological Diversity, and the Sendai Framework for Risk Reduction. By presenting evidence for how EO can contribute to innovative opportunities and data synergies at scale, the paper discusses opportunities and challenges for a more solution-led approach to sustainable coastal management.

show abstract

Uncertainties and applications of satellite-derived coastal water quality products

Cited by 84 publications

References 265 publications

Water Quality Drivers in 11 Gulf of Mexico Estuaries

Water Quality Drivers in 11 Gulf of Mexico Estuaries

Correlation of Remotely Sensed Surface Reflectance With Forcing Variables in Six Different Estuaries

Earth observation applications for coastal sustainability: potential and challenges for implementation

Contact Info

Product

Resources

About