Modelling the inherent optical properties and estimating the constituents׳ concentrations in turbid and eutrophic waters

Gokul, Elamurugu Alias; Shanmugam, Palanisamy; Sundarabalan, Balasubramanian; Sahay, Arvind; Chauhan, Prakash

doi:10.1016/j.csr.2014.05.013

Cited by 24 publications

(14 citation statements)

References 49 publications

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“…Therefore, to improve the ocean colour estimates, it is essential to develop the robust regional algorithms for the coastal waters. An accurate estimation of ocean colour of bio-optical variables in the complex coastal waters is still a challenging task (Gokul et al, 2014). The bio-optical properties of the coastal water bodies are understudied (Tilstone et al, 2013;Ferreira et al, 2014) due to the optical complexity of the waters.…”

Section: Introductionmentioning

confidence: 99%

Seasonal variability in bio-optical properties along the coastal waters off Cochin

Vishnu

Shaju

Tiwari

et al. 2018

International Journal of Applied Earth Observation and Geoinfor

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Strong seasonal upwelling, downwelling, changes in current patterns and the volume of freshwater discharge from Cochin Estuary defines the coastal waters off Cochin. These coastal waters were investigated through monthly sampling efforts during March 2015 to February 2016 to study the seasonal and spatial variability in bio-optical properties for the four different seasons mainly Spring Inter Monsoon (SIM), South West Monsoon (SWM), Fall Inter Monsoon (FIM) and Winter Monsoon (WM). The Barmouth region is the meeting place where freshwater from Cochin Estuary directly enters to the sea through a single narrow outlet, was dominated by highly turbid waters during the entire period of study. Among the four seasons, chlorophyll a (Chl_a) concentration showed a high value during SWM, ranged from 2.90 to 11.66 mg m −3 with an average value of 6.56 ± 3.51 mg m −3. During SIM the distribution of coloured dissolved organic matter (CDOM) is controlled by decomposition of phytoplankton biomass and the river discharge, whereas during SWM the temporal distribution of CDOM is controlled only by river discharge. The highest value for CDOM spectral slope (S CDOM) was observed during SWM, ranged from 0.013 to 0.020 nm −1 with an average value of 0.015 ± 0.002 nm −1. During WM, the high S CDOM with lower a CDOM (443) indicates the photo-degradation affects the absorption characteristics of CDOM. The observed nonlinearity between Chl_a and the ratio of phytoplankton absorption a ph (443)/a ph (670) indicating the packaging effect and changes in the intercellular composition of pigments. During the study period, a ph (670) was strongly correlated with Chl_a than a ph (443), which explains the accessory pigment absorption dominating more than Chl_a in the blue part of the spectrum. Similarly, the results obtained from seasonal bio-optical data indicating that Chl_a significantly contributes light attenuation of the water column during SIM, whereas detritus (a d) significantly contributes light attenuation during SIM and WM. During the study period, the relative absorption of detritus materials dominates the relative absorption of phytoplankton and CDOM at 443, 555 and 670 nm wavelengths.

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Section: Introductionmentioning

confidence: 99%

Seasonal variability in bio-optical properties along the coastal waters off Cochin

Vishnu

Shaju

Tiwari

et al. 2018

International Journal of Applied Earth Observation and Geoinfor

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“…This bio‐optical algorithm was demonstrated to be very effective in terms of accurate estimation of chlorophyll and discriminating algal bloom patches in coastal waters rather than using global algorithms (e.g., OC3 and OC4v4). Inherent optical properties such as absorption ( a ( λ ) = a w ( λ )+ a p ( λ )+ a cdom ( λ )) and backscattering ( b b ( λ ) = b w ( λ )+ b p ( λ )) were derived from the existing models [ Shanmugam et al ., ; Gokul et al ., ; Varunan and Shanmugam , ; Sundarabalan and Shanmugam , ]. The pure water absorption and backscattering coefficients were added with these particulate terms to obtain the respective total absorption and backscattering coefficients.…”

Section: Methodsmentioning

confidence: 99%

“…The predictive model takes the form as,

a_{c d o m / d} = a_{c d o m / d} (λ_{r}) \times e^{- S (λ - λ_{r})}

where λ r is the reference wavelength at 443 nm and S is the spectral slope coefficient (nm −1 ). The a d ( 443 ) and a cdom ( 443 ) values are estimated by empirical methods [ Gokul et al ., ] that relate to the remote sensing reflectance in equations and ,

a_{d} (443) = 0.3314 \times {true(\frac{R_{r s} true(620 true)}{R_{r s} (490)} true)}^{1.516}

a_{c d o m} (443) = 0.1005 \times {true(\frac{R_{r s} true(555 true)}{R_{r s} (443)} true)}^{1.4499}

…”

Section: Approachmentioning

confidence: 99%

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An optical system for detecting and describing major algal blooms in coastal and oceanic waters around India

Gokul

Shanmugam

2016

JGR Oceans

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An optical system is developed with the aim to detect and monitor three major algal blooms (including harmful algal blooms ''HABs'') over ecologically relevant scales around India and to strengthen algal forecasting system. This system is designed to be capable of utilizing remote sensing, in situ, and radiative transfer techniques to provide species-specific data necessary for increasing capabilities of an algal forecasting system. With the ability to measure in-water optical properties by means of remote sensing and in situ observations, the optical system developed infers the desired phytoplankton signal from spectral distributions and utilize these data in a numerical classification technique to generate species-specific maps at given spatial and temporal scales. A simple radiative transfer model is adopted for this system to provide a means to optimally interpolate to regions with sparse in situ observation data and to provide a central component to generate in-water optical properties from remotely sensed data. For a given set of inherent optical properties along with surface and bottom boundary conditions, the optical system potentially provides researchers and managers coverage at different locations and depths for tracking algal blooms in the water column. Three major algal blooms focused here include Noctiluca scintillans/miliaris, Trichodesmium erythraeum, and Cochlodinium polykrikoides, which are recurring events in coastal and oceanic waters around India. Because satellite sensors provide a synoptic view of the ocean, both spatially and temporally, our initial efforts tested this optical system using several MODIS-Aqua images and ancillary data. Validation of the results with coincident in situ data obtained from either surface samples or depth samples demonstrated the robustness and potential utility of this approach, with an accuracy of 80-90% for delineating the presence of all three blooms in a heterogeneous phytoplankton community. Despite its limitation in detecting specific species during their prebloom phases and indicating whether a particular bloom is toxic or harmful, the proposed optical system will provide managers with the specific phytoplankton bloom maps to structure monitoring efforts and a powerful tool for studying the dynamics of algal blooms at various temporal and spatial scales.

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“…The concentration of water constituents can fluctuate significantly over a short time period, making it necessary to continuously monitor bodies of water [1]. Unlike in situ campaigns that provide point measurements, remote sensing techniques can detect the spatial and temporal variation in water bodies [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of MERIS Chlorophyll-a Retrieval Processors in a Complex Turbid Lake Kasumigaura over a 10-Year Mission

et al. 2017

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Abstract:The chlorophyll-a (Chla) products of seven processors developed for the Medium Resolution Imaging Spectrometer (MERIS) sensor were evaluated. The seven processors, based on a neural network and band height, were assessed over an optically complex water body with Chla concentrations of 8.10-187.40 mg·m −3 using 10-year MERIS archival data. These processors were adopted for the Ocean and Land Color Instrument (OLCI) sensor. Results indicated that the four processors of band height (i.e., the Maximum Chlorophyll Index (MCI_L1); and Fluorescence Line Height (FLH_L1)); neural network (i.e., Eutrophic Lake (EUL); and Case 2 Regional (C2R)) possessed reasonable retrieval accuracy with root mean square error (R 2 ) in the range of 0.42-0.65. However, these processors underestimated the retrieved Chla > 100 mg·m −3 , reflecting the limitation of the band height processors to eliminate the influence of non-phytoplankton matter and highlighting the need to train the neural network for highly turbid waters. MCI_L1 outperformed other processors during the calibration and validation stages (R 2 = 0.65, Root mean square error (RMSE) = 22.18 mg·m −3 , the mean absolute relative error (MARE) = 36.88%). In contrast, the results from the Boreal Lake (BOL) and Free University of Berlin (FUB) processors demonstrated their inadequacy to accurately retrieve Chla concentration > 50 mg·m −3 , mainly due to the limitation of the training datasets that resulted in a high MARE for BOL (56.20%) and FUB (57.00%). Mapping the spatial distribution of Chla concentrations across Lake Kasumigaura using the seven processors showed that all processors-except for the BOL and FUB-were able to accurately capture the Chla distribution for moderate and high Chla concentrations. In addition, MCI_L1 and C2R processors were evaluated over 10-years of monthly measured Chla as they demonstrated the best retrieval accuracy from both groups (i.e., band height and neural network, respectively). The retrieved Chla of MCI_L1 was more accurate at tracking seasonal and annual variation in Chla than C2R, with only slight overestimation occurring during the springtime.

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Modelling the inherent optical properties and estimating the constituents׳ concentrations in turbid and eutrophic waters

Cited by 24 publications

References 49 publications

Seasonal variability in bio-optical properties along the coastal waters off Cochin

Seasonal variability in bio-optical properties along the coastal waters off Cochin

An optical system for detecting and describing major algal blooms in coastal and oceanic waters around India

Evaluation of MERIS Chlorophyll-a Retrieval Processors in a Complex Turbid Lake Kasumigaura over a 10-Year Mission

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