Water Diffuse Attenuation Coefficient Research Articles

Global daily gap-free ocean color products from multi-satellite measurements

Gap-free global chlorophyll-a (Chl-a) concentration images derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20 are now available online in near-real-time for the ocean color community. With the data fusion of Chl-a from the two satellite sources, missing pixels caused by cloud, sun glint contamination, high satellite viewing angles, and other unfavorable conditions are completely filled using the Data Interpolating Empirical Orthogonal Function (DINEOF) method. Our further studies show that adding more data from additional satellite sensors can remarkably improve the spatial coverage of the merged ocean color products, provide more ocean features over coastal and inland waters, and enhance the accuracy of the gap-free data. Since the launch of the Sentinel-3A and Sentinel-3B satellites, the onboard Ocean and Land Colour Instrument (OLCI) sensors have been providing global ocean color product data. In this work, we recruit the OLCI-Sentinel-3A to join the two VIIRS sensors to produce a three-sensor merged ocean color dataset, and further derive global gap-free images using the DINEOF method. It is found that adding OLCI data as the input source significantly enhances the spatial features of high Chl-a by ∼10–20% in productive coastal regions and inland lakes. Additionally, the first-ever dataset of global gap-free suspended particulate matter (SPM) and water diffuse attenuation coefficient at 490 nm (Kd(490)) is also generated using the three-sensor merged data. Results show that Kd(490) and SPM have similar spatial patterns as that of Chl-a in the major ocean basins, and that SPM can provide more details of the spatial variations than those of Kd(490) in the center of the ocean basin and coastal oceans. Global gap-free Chl-a, Kd(490), and SPM products provide important and useful water quality information particularly over global productive ocean/water regions.

Deriving VIIRS High-Spatial Resolution Water Property Data over Coastal and Inland Waters Using Deep Convolutional Neural Network

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been a reliable source of ocean color data products, including five moderate (M) bands and one imagery (I) band normalized water-leaving radiance spectra nLw(λ). The spatial resolutions of the M-band and I-band nLw(λ) are 750 m and 375 m, respectively. With the technique of convolutional neural network (CNN), the M-band nLw(λ) imagery can be super-resolved from 750 m to 375 m spatial resolution by leveraging the high spatial resolution features of I1-band nLw(λ) data. However, it is also important to enhance the spatial resolution of VIIRS-derived chlorophyll-a (Chl-a) concentration and the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), as well as other biological and biogeochemical products. In this study, we describe our effort to derive high-resolution Kd(490) and Chl-a data based on super-resolved nLw(λ) images at the VIIRS five M-bands. To improve the network performance over extremely turbid coastal oceans and inland waters, the networks are retrained with a training dataset including ocean color data from the Bohai Sea, Baltic Sea, and La Plata River Estuary, covering water types from clear open oceans to moderately turbid and highly turbid waters. The evaluation results show that the super-resolved Kd(490) image is much sharper than the original one, and has more detailed fine spatial structures. A similar enhancement of finer structures is also found in the super-resolved Chl-a images. Chl-a filaments are much sharper and thinner in the super-resolved image, and some of the very fine spatial features that are not shown in the original images appear in the super-resolved Chl-a imageries. The networks are also applied to four other coastal and inland water regions. The results show that super-resolution occurs mainly on pixels of Chl-a and Kd(490) features, especially on the feature edges and locations with a large spatial gradient. The biases between the original M-band images and super-resolved high-resolution images are small for both Chl-a and Kd(490) in moderately to extremely turbid coastal oceans and inland waters, indicating that the super-resolution process does not change the mean values of the original images.

Assessment of Water Quality Along the Southeast Coast of India During COVID-19 Lockdown

The COVID-19 pandemic has affected the entire world and has had a devastating impact on both lives and livelihoods in India. The only way to defeat the rapid spread of COVID-19, is to shut down socio-economic activities and to maintain minimal human interaction with the implementation of a lockdown. Such lockdowns have manifested in a pollution curtailment in almost all spheres of the planet, including in marine pollution. Quantifying this decrease in pollution levels enables the scientific community to assess the contribution of anthropogenic (especially non-essential) activities to global/regional pollution levels. This paper aims to study the impact of the stringent lockdown period (phase 1 and 2) on coastal water quality along the Chennai coast of India, by analyzing suspended matter concentration (SPM), a key element of water quality and diffuse attenuation coefficient, Kd(490), using LANDSAT-8 Operational Land Imager (OLI) data. LANDSAT-8/OLI, L1TP scenes were subjected to radiometric calibration and atmospheric correction to derive surface reflectance values from raw digital numbers using ACOLITE software and a brief insight has been given for the Dark Spectrum Fitting algorithm used in ACOLITE. SPM concentration decreased by 15.48 and 37.50% in the Chennai and Ennore ports, respectively, due to minimal vessel movement and cargo handling. The stringent lockdown led to the operation of fewer thermal plant units, thus less fly ash was emanated, resulting in a 28.05% reduction in SPM levels over Ennore creek. As industrial and commercial activities subsided, the city’s water bodies became clearer than they were just a fortnight prior to the lockdown, with a reduction of 22.26% of SPM in Adyar and 33.97% in Cooum riverine estuaries. Decrease in Kd(490) showed a positive relationship with SPM and thus improved coastal water quality because of the reduction of SPM during this period. The variations in PM2.5 and PM10 concentrations were studied using National Air Quality Monitoring Programme (NAMP) data and reduced levels in particulate matter concentration (PM2.5 and PM10) for the Adyar residential area (24.38 and 28.43%) and for the Nungampakkam commercial area (36.09 and 67.18%) were observed. A significant reduction in PM2.5 concentration (45.63%) was observed in the Ennore-Manali Industrial region.

Water property in high-altitude Qinghai Lake in China

Qinghai Lake in China, which is located at an altitude of 3260 ​m, is the highest inland lake among the 50 largest lakes in the world. Therefore, satellite measurement of water quality is the most important and feasible tool for routinely assessing the water property and its variations in Qinghai Lake. We derive the normalized water-leaving radiance spectra nLw(λ) in Qinghai Lake from measurements of the Visible Infrared Imaging Radiometer Suite (VIIRS), after accurately computing the top-of-atmosphere Rayleigh radiances in the satellite Level-1 to Level-2 ocean color data processing. Satellite-derived nLw(λ) spectra, chlorophyll-a (Chl-a) concentration, and the water diffuse attenuation coefficient at 490 ​nm, Kd(490), in the period of 2012–2018 are used to evaluate and understand the dynamics of water properties in Qinghai Lake. Results show that VIIRS-measured nLw(λ) spectra match quite well with the in situ data, e.g., the mean and median ratios of the VIIRS-derived and in situ-measured nLw(λ) at 443 ​nm are 0.9741 and 0.9898, respectively. Enhanced nLw(λ) at 486 ​nm and 551 ​nm can be observed from satellite-derived nLw(λ) spectra for the entire lake. VIIRS-derived nLw(λ) spectra show significant seasonal cycles. High nLw(λ) values occur in July while low values occur in April. Results also show the seasonal and interannual changes of Chl-a and Kd(490) in Qinghai Lake. Low Chl-a and Kd(490) are normally observed in April, and they typically peak in the early summer. Peculiarly, however, anomaly high values in Chl-a and Kd(490) occurred in June 2016. The analysis of empirical orthogonal functions (EOFs) shows the dominant modes for Chl-a and Kd(490) are interannual modes that account for about 79.1% and 31.5% of the their total variances, respectively. The second EOF mode for Chl-a and Kd(490) shows the seasonal changes, and contributes to about 6.1% and 14.0% of their respective total variances.

Water properties in the La Plata River Estuary from VIIRS observations

In this study, observations from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) between 2012 and 2018 are used to characterize and quantify water optical properties in the La Plata River Estuary (or Río de la Plata Estuary). Satellite-measured normalized water-leaving radiance spectra nLw(λ) are found to be similar with the peak at the 671 nm red band in the inner and mid estuaries, while nLw(λ) spectra peak at the 551 nm green band in the outer estuary. Remarkable seasonal and inter-annual variability are also observed in the La Plata River Estuary. The austral autumn (March–May) is found to be the most turbid season. An enhanced radiance ratio nLw(745)/nLw(671) is also found to occur during the austral autumn season in the inner and mid estuaries. The La Plata River Estuary had the most turbid water in 2012 in terms of the satellite-measured water diffuse attenuation coefficient at 490 nm Kd(490) in the inner and mid estuaries. The low Kd(490) in the inner and mid estuaries during 2015–2016 coincided with the strong 2015–2016 El Niño event. The first and second empirical orthogonal function (EOF) modes account for about 34.9% and 27.0% of the total Kd(490) variance in the La Plata River Estuary, respectively. In addition, the Kd(490) variation in the inner and mid estuaries is out of phase with that in the outer estuary. The winds, rainfall, and river discharge are attributed to the first and second EOF modes of the Kd(490) in the La Plata River Estuary.

Analysis of ocean diurnal variations from the Korean Geostationary Ocean Color Imager measurements using the DINEOF method

High-frequency images of the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)) derived from the Korean Geostationary Ocean Color Imager (GOCI) provide a unique opportunity to study diurnal variation of water turbidity in coastal regions of the Bohai Sea, Yellow Sea, and East China Sea. However, there are many missing pixels in the original GOCI-derived Kd(490) images due to clouds and various other reasons. Data Interpolating Empirical Orthogonal Function (DINEOF) is a method to reconstruct missing data in geophysical datasets based on the Empirical Orthogonal Function (EOF). It utilizes both temporal and spatial coherencies of data to infer a solution at the missing locations. In this study, the DINEOF is applied to GOCI-derived Kd(490) data in the Yangtze River mouth and the Yellow River mouth regions, and the DINEOF reconstructed Kd(490) data are used to fill in the missing pixels. In fact, DINEOF has been used to fill in gaps in ocean color chlorophyll-a and turbidity data from the Sea-viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) in previous studies. Our GOCI validation results show that the bias between the reconstructed data and the original Kd(490) value is quite small (<∼5%). The standard deviation of the reconstructed/original ratio is ∼0.25 and ∼0.30 for the mouths in the Yangtze River and Yellow River, respectively. In addition, GOCI high temporal resolution measurements in Kd(490) can capture sub-diurnal variation due to the tidal forcing. The spatial patterns and temporal functions of the first three EOF modes are also examined. The first EOF mode characterizes the general mean spatial distribution of the region, while the second and third EOF modes represent the variations due to the tidal forcing in the region.

Destriping algorithm for improved satellite-derived ocean color product imagery.

While modern multi-detector sensors offer a much improved image resolution and signal-to-noise ratio among other performance benefits, the multi-detector arrangement gives rise to striping in satellite imagery due to various sources, which cannot be perfectly corrected by sensor calibration. Recently, Bouali and Ignatov (2014) [J. Atmos. Oceanic Technol., 31, 150-163 (2014)] introduced a new approach to remove relatively small detector performance-related striping from thermal infrared bands for improved sea surface temperature data. We show that this methodology, with appropriately chosen parameters and adjustments, can also be applied to remove striping of a much larger variance from the solar reflective band data. Specifically, we modify and apply this new approach to remove striping from satellite-derived normalized water-leaving radiance spectra nLw(λ) obtained from solar reflective bands. It is important that the destriping approach not be applied to the top-of-atmosphere radiances. The results show a significant improvement in image quality for both nLw(λ) spectra and nLw(λ)-derived ocean biological and biogeochemical products such as chlorophyll-a concentration, and the water diffuse attenuation coefficient at the wavelength of 490 nm Kd(490).

Tidal effects on ecosystem variability in the Chesapeake Bay from MODIS-Aqua

Eight-year ocean color observations between 2002 and 2009 from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the satellite Aqua are used to quantitatively assess the tidal effects on variability of ocean's optical, biological, and biogeochemical properties in the Chesapeake Bay. We demonstrate that tidal variation in the lower Chesapeake Bay is one of the important ocean processes that drive significant changes of the ocean's optical and biogeochemical properties. Normalized water-leaving radiance spectra (nLw(λ)), water diffuse attenuation coefficient at the wavelength of 490nm (Kd(490)), and total suspended sediment (TSS) concentration show significant tidal variations in the lower Chesapeake Bay. Indeed, in the lower Bay region, Kd(490) increases from 0.9m−1 under low tidal current conditions at 0.10–0.15m/s to 1.35m−1 under high tidal current conditions at 0.45–0.50m/s, while chlorophyll-a concentration in the lower Bay region decreases slightly with an increase of the tidal current. Tide-driven variability in Kd(490) and TSS in the lower Bay is similar to and slightly larger than the seasonal variability in the region. On the other hand, different from the variability in the lower Bay, the tidal effects on the ecosystem are small and negligible in the middle and a large part of upper Chesapeake Bay regions.

Long-term distribution patterns of remotely sensed water quality parameters in Chesapeake Bay

Chesapeake Bay is the largest and one of the most productive estuaries in the U.S., where long-term monitoring and assessment of its water quality are necessary to understand trends and events in order to support management decisions. Significant progress has been made during the past decade in developing remote sensing algorithms for estimating two key water quality parameters, chlorophyll-a concentration (Chla, mg m−3) and diffuse light attenuation coefficient at 490 nm (Kd (490), m−1), from satellite ocean color measurements in oceanic, coastal, and estuarine waters. Yet deriving a robust Chla data product for Chesapeake Bay still remains a challenge because of its complex optical properties. Here, a recently developed algorithm approach (Red–Green Chlorophyll Index or RGCI, based on red–green remote-sensing reflectance (Rrs (λ)) ratios) was tested, validated, and applied to Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to establish a 14-year (September 1997 to December 2011) Chla Environmental Data Record (EDR). The new approach showed significant improvement over the traditional blue–green Rrs (λ) band-ratio algorithms (e.g., OC4, OC3M), with consistent performance for MODIS (mean relative error = 40.9%, mean ratio = 1.09) and SeaWiFS (MRE = 45.8%, mean ratio = 1.09) for Chla ranging between 1 and 50 mg m−3. Anomaly and EOF analyses revealed strong spatial gradients, seasonality, and climate-driven inter-annual changes in the satellite-based Chla EDR. These changes were highly correlated with satellite-based Kd (490) EDR, leading to the development of a Water Quality Decision Matrix (WQDM) and providing support to on-going nutrient reduction management programs for this estuary.

Water properties in Chesapeake Bay from MODIS-Aqua measurements

This study evaluates the performance of ocean color products derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua using the standard near-infrared (NIR) and the shortwave infrared (SWIR)-based atmospheric correction algorithms in the Chesapeake Bay. The MODIS-Aqua-derived normalized water-leaving radiances, nLw(λ), and chlorophyll-a (Chl-a) data are compared with in situ radiometric measurements from the NASA SeaWiFS Bio-optical Archive and Storage System (SeaBASS) database and Chl-a data from the Chesapeake Bay Water Quality Database. Results show that, using the NIR-SWIR combined ocean color data processing, improved nLw(λ) and Chl-a data products can be produced in the Chesapeake Bay. However, Chl-a data are still overestimated in some Chesapeake Bay regions, in particular, in the upper bay region where waters are strongly influenced by the total suspended sediment (TSS) concentration. Specifically, using the NIR-SWIR approach, mean ratios of MODIS-derived and in situ-measured nLw(λ) at wavelengths of 412, 443, 488, 531, 551, and 667nm for the Chesapeake Bay are 1.288, 1.093, 0.998, 0.946, 0.908, and 0.865, respectively, while mean Chl-a values over the region from satellite-derived and in situ-measure data are 11.14 and 10.28mg·m−3, respectively. Based on a strong correlation relationship between TSS and water diffuse attenuation coefficient, a regional TSS algorithm for the Chesapeake Bay has been developed and validated, with mean ratio of 1.064 between MODIS-derived and in situ-measured TSS data. Therefore, using the NIR-SWIR algorithm for MODIS-Aqua ocean color data processing, nLw(λ), Chl-a, and TSS data from 2002 to 2010 for the Chesapeake Bay have been generated and used for characterizing the water properties in the region, showing strong seasonal and interannual variability, as well as important spatial variations in the region.

Spring-neap tidal effects on satellite ocean color observations in the Bohai Sea, Yellow Sea, and East China Sea

[1] Eight-year ocean color observations between 2002 and 2009 from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite are used to quantitatively assess the spring-neap tidal effects on variability of ocean optical and biogeochemical properties in the Bohai Sea, Yellow Sea, and East China Sea. We demonstrate that spring-neap tidal variation is one of important ocean processes that drive both the synoptic-scale and mesoscale changes of the ocean optical, biological, and biogeochemical properties in the coastal region. Normalized water-leaving radiance spectra (nLw(λ)), water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), and total suspended matter (TSM) concentration show significant spring-neap variations in the coastal region within a lunar cycle of 29.53 days. In the open ocean, however, spring-neap tidal effects on ocean color data are negligible. The entire areal coverage of the turbid waters (Kd(490) > 0.3 m−1) showing significant spring-neap tidal variations is ∼4–5 × 105 km2. Similar coverage of moderately turbid waters (0.1 < Kd(490) ≤ 0.3 m−1) is also impacted by the spring-neap tides. The magnitude of the spring-neap tidal effects on the variations of the satellite ocean color properties, e.g., Kd(490) and TSM, is in the same order as the seasonal variations in the coastal region. Highest Kd(490) and largest turbid water coverage lag the new moon (or full moon) about 2–3 days, while the lowest Kd(490) and smallest turbid water coverage are also ∼2–3 days behind the one-quarter (or three-quarter) moon. This is attributed to the seawater inertia and the friction against the seabed as well as the sediment resuspension process.

Ocean sand ridge signatures in the Bohai Sea observed by satellite ocean color and synthetic aperture radar measurements

Satellite measurements from Synthetic Aperture Radar (SAR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua platform are used to study the ocean sand ridges in the eastern Bohai Sea in China. Even though the imaging mechanisms for SAR and MODIS-Aqua remote sensing are different, the sand ridges are shown to have exactly the same patterns in images from both sensors. Therefore, the location, extension and coverage of the ocean sand ridges can be detected and cross-examined by both SAR and MODIS-Aqua observations. Satellite images show quite different sand ridge distribution pattern from the published bathymetry map (based on in situ data) that shows six sand ridges in the area. 10 finger-shaped sand ridges are identified from satellite observations. The tidal-current/sand-ridge interaction driven physical and optical changes are assessed and evaluated. The existence of sand ridges causes enhanced water diffuse attenuation coefficient K d (490) and elevated normalized water-leaving radiance at the red and near-infrared (NIR) wavelengths. The sea surface over the sand ridges experiences significant seasonal variability of water turbidity and shows remarkable differences from nearby ocean regions. During winter, K d (490) values are about 2–3 m − 1 over the ridges, while the maximum K d (490) in the neighboring oceans is approximately 1.5 m − 1 . In summer, the enhancement of the sea surface turbidity is less significant than that which occurs in winter.

Near-Real-Time Ocean Color Data Processing Using Ancillary Data From the Global Forecast System Model

This paper investigates the improvements to the quality of ocean color data using an appropriate choice of ancillary data for National Oceanic and Atmospheric Administration (NOAA) operational ocean color data processing, which requires routine ocean color product production in near real time. The ancillary data, such as the total column ozone amount, sea surface wind speed, atmospheric pressure, and total column water-vapor amount, are required for satellite ocean color data processing for deriving ocean color products, e.g., normalized water-leaving radiance spectra data, chlorophyll-a concentration, water diffuse attenuation coefficient, etc. Currently, NOAA's CoastWatch program uses the climatology ancillary data for the near-real-time ocean color data processing. Alternative ancillary data sets that can replace the climatology data for the near-real-time ocean color data processing have been investigated and studied. The studies were carried out from four selected NOAA CoastWatch regions covering the U.S. coastal and Hawaii regions and for four months (January, April, July, and October), representing the four seasons. Based on the evaluation results, we propose to use the ancillary data produced from the Global Forecast System (GFS) model for the NOAA operational ocean color data processing, as well as for any other near-real-time data processing that requires ancillary data inputs. The effects of using the GFS model data on the accuracy of the derived ocean color products are also investigated and discussed.

Water property monitoring and assessment for China's inland Lake Taihu from MODIS-Aqua measurements

We provide results of quantitative measurements and characterization for inland freshwater Lake Taihu from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua. China 's Lake Taihu, which is located in the Yangtze River delta in one of the world 's most urbanized and heavily populated areas, contains consistently highly turbid waters in addition to frequent large seasonal algae blooms in various lake regions. Thus, satellite data processing requires use of the shortwave infrared (SWIR) atmospheric correction algorithm. Specifically for Lake Taihu, an iterative SWIR-based atmospheric correction algorithm has been developed and proven to provide reasonably accurate water-leaving radiance spectra data. Using MODIS-Aqua measurements, the blue-green algae bloom in Lake Taihu in 2007 has been studied in detail, demonstrating the importance and usefulness of satellite water color remote sensing for effectively monitoring and managing a bloom event. Seasonal and interannual variability, as well as spatial distributions, of lake water properties were studied and assessed using the MODIS-Aqua measurements from 2002 to 2008. Results show that overall waters in Lake Taihu are consistently highly turbid all year round, with the winter and summer as the most and least turbid seasons in the lake, respectively. Extremely turbid waters in the winter are primarily attributed to strong winter winds that lead to significant amounts of total suspended sediment (TSS) in the water column. In addition, MODIS-Aqua–measured water-leaving radiance at the blue band is consistently low in various bay regions in Lake Taihu, indicating high algae concentration in these regions. Climatological water property maps, including normalized water-leaving radiance spectra nL w (λ), chlorophyll-a concentration, and water diffuse attenuation coefficient at the wavelength of 490 nm ( K d (490)), are derived from all MODIS-Aqua data from 2002 to 2008 for Lake Taihu, showing overall spatial distribution features for the lake water property.

Satellite observations of optical and biological properties in the Korean dump site of the Yellow Sea

With the standard near-infrared (NIR) atmospheric correction algorithm for ocean color data processing, a high chlorophyll- a concentration patch was consistently observed from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua platform in the middle of the Yellow Sea during the spring (end of March to early May). This prominent patch was not observed in the historical ocean color satellite imageries in late 1970s to early 1980s, and a location corresponding to this patch has been used as a Korean dump site since 1988. At the same time, MODIS chlorophyll- a concentrations derived using the shortwave infrared (SWIR) atmospheric correction algorithm developed for the ocean color satellite data in turbid coastal or high-productive ocean waters were significantly reduced. Comparison between in situ and MODIS chlorophyll- a measurements shows that the chlorophyll- a from the MODIS-Aqua products using the standard-NIR atmospheric correction algorithm is significantly overestimated. The images of the MODIS-derived normalized water-leaving radiance spectra and water diffuse attenuation coefficient data using the NIR-SWIR-based atmospheric correction approach show that absorption and scattering by organic and inorganic matter dumped in the Korean dump site have strongly influenced the satellite-derived chlorophyll- a data. Therefore, the biased high chlorophyll- a patch in the region is in fact an overestimation of chlorophyll- a values due to large errors from the standard-NIR atmospheric correction algorithm. Using the NIR-SWIR algorithm for MODIS-Aqua ocean color data processing, ocean color products from 2002 to 2008 for the Korean dump site region have been generated and used for characterizing the ocean optical and biological properties. Results show that there have been some important changes in the seasonal and interannual variations of phytoplankton biomass and other water optical and biological properties induced by colored dissolved organic matters, as well as suspended sediments.

K&lt;sub&gt;PAR&lt;/sub&gt;: An optical property associated with ambiguous values

In studies of aquatic environments, an optical property, KPAR, which represents the diffuse attenuation coefficient of Photosynthetic Available Radiation (PAR), is used frequently. Because water's diffuse attenuation coefficient is highly spectral dependent and PAR is spectrally narrowing to wavelengths with less attenuation coefficients with increasing depth, this KPAR is significantly depth dependent in the upper water column even for well-mixed waters. In this article, with an aim for more reliable attenuation products and more accurate description of PAR profiles, the ambiguity associated with KPAR is highlighted, and the proper representation of the vertical variation of KPAR is advocated.

Preliminary optical classification of lakes and coastal waters in Estonia and south Finland

A preliminary optical classification of lakes in Estonia and south Finland which can also be used for small bays of the Baltic Sea is elaborated. The classification is based on the optical properties of water (diffuse attenuation coefficient, diffuse reflectance) and parameters that are routinely monitored in water bodies (Secchi depth, concentration of chlorophyll-a, total suspended matter and yellow substance). The data complex used for our classification covers different types of water ecosystems (ranging from oligotrophic to hypertrophic) and the variability of water constituent concentrations in the ice-free period in Estonia and south Finland. Using cluster analysis, we found 5 optical classes of waters: clear (C), moderate (M), turbid (T), very turbid (V) and brown (B). There is satisfactory correspondence between class of water, shape of diffuse attenuation coefficient and diffuse reflectance spectra and trophic state of the lakes.

A remote sensing method for resolving depth and subpixel composition of aquatic benthos

The problem of subpixel heterogeneity in cover types has been addressed in terrestrial environments by the application of linear spectral unmixing techniques. However, in aquatic systems the interceding depth of water causes the apparent reflectance of the substrate to diverge from a linear model, and if depth is unknown these methods cannot be applied. A new technique is presented in which the conventional spectral unmixing method has been modified to calculate depth at each pixel in addition to the proportions of substrate type. The technique requires knowledge of the reflectance spectra of m pure substrata in n (n ≫ m) spectral bands at depth 0 and the water diffuse attenuation coefficients for the site in the same bands. Depth, z, can be entirely unknown. The method is comparable to “classical” spectral unmixing and proceeds by performing a Gaussian elimination for endmember quantities and then solving the remaining nonlinear function of z for f(z) = 0 by successive approximation. Computer‐based models are used to test the technique with realistic water diffuse attenuation coefficients and random spectra and actual spectra of coral reef substrata. The robustness of the technique is assessed against three forms of introduced error: measurement errors on the spectra to be unmixed, differences between the true endmember spectra and those used in the analysis, and measurement error on the water diffuse attenuation coefficients. The results of these tests imply the technique is sufficiently robust for use on real data. Furthermore, spectral unmixing of aquatic systems appears to be relatively insensitive to inaccuracies in depth estimation and offers great utility for benthic mapping.

Significance of pelagic and benthic primary production in two shallow coastal lagoons of different degrees of eutrophication in the southern Baltic Sea

AME Aquatic Microbial Ecology Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials AME 20:273-284 (1999) - doi:10.3354/ame020273 Significance of pelagic and benthic primary production in two shallow coastal lagoons of different degrees of eutrophication in the southern Baltic Sea Jürgen Meyercordt*, Sabine Gerbersdorf, Lutz-Arend Meyer-Reil Institut für Ökologie, Ernst-Moritz-Arndt-Universität Greifswald, 18565 Kloster/Hiddensee, Germany *E-mail: meyercor@rz.uni-greifswald.de ABSTRACT: Primary production by pelagic and benthic microalgae was measured in 2 shallow coastal lagoons in the southern Baltic Sea by in situ and laboratory incubations to quantify the significance of these 2 major groups of primary producers in absolute and relative terms. Pelagic primary production rates per volume at saturating light conditions were 7 to 12 times higher at the polytrophic location Kirr-Bucht (Darss-Zingst Bodden) than at the meso-/eutrophic location Rassower Strom (Nordrügensche Bodden). Chlorophyll a specific primary production rates, however, were in the same range at both locations, except for 1 situation in spring which is explicitly discussed. The pelagic chlorophyll a specific maximum light utilization coefficient (a*) tended towards higher values in Kirr-Bucht samples, which can be interpreted as an adaptation to a lower supply of irradiance. Pelagic and benthic primary production varied seasonally, with highest rates occurring in June/July. A calculation of short-term variability due to cloud-modulated availability of irradiance revealed reductions of pelagic and benthic gross production (GP) rates on overcast days, compared to bright days, in the range of 26 to 69% and 62 to 82%, respectively. Net community production (NP) rates were more severely reduced than GP rates on overcast days. Benthic NP was generally reduced to below zero on overcast days, whereas it was mostly positive on bright days at both locations. To evaluate the significance of the different optical properties of both types of water (diffuse vertical attenuation coefficient, k = 3.3 to 3.7 and 0.5 to 0.7 m-1 at Kirr-Bucht and Rassower Strom, respectively) for primary production, the benthic and pelagic contributions at both sites were calculated regarding a water depth of 2 m, which is about the mean depth of the Bodden systems. This standardization revealed obvious differences in basic conditions for primary production which remained undetected when the comparison of the 2 sites was based on the water depths in which the in situ incubations had been carried out (0.6 and 3.4 m at Kirr-Bucht and Rassower Strom, respectively). In meso-/eutrophic Rassower Strom at a depth of 2 m, benthic GP would contribute about 30 to 45% to the total GP of microalgae, depending on weather conditions and seasons. At the same depth in polytrophic Kirr-Bucht, the microalgae on the sediment surface would account for only 0.3% or less of total GP. This demonstrates that optical properties of the water, which are closely related to the trophic state of the system, exert strong control on varying proportions of productivity, attributable to planktonic versus benthic microalgal communities. It can be concluded from the modeled data that the difference between both locations will be most prominent during periods of low supply of radiant energy, like on overcast days. KEY WORDS: Primary production · Phytoplankton · Microphytobenthos · Irradiance · Eutrophication · Estuary · Baltic Sea Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in AME Vol. 20, No. 3. Publication date: December 30, 1999 Print ISSN: 0948-3055; Online ISSN: 1616-1564 Copyright © 1999 Inter-Research.