Oceanologia No. 63 (4 / 21)


Contents


In memoriam


Original research article


Original research article



Role of riverine inputs, low saline plume advection and mesoscale physical processes in structuring the Chlorophyll a distribution in the western Bay of Bengal during Fall Inter Monsoon
Oceanologia 2021, 63(4), 403-419
https://doi.org/10.1016/j.oceano.2021.04.004

Jagadeesan Loganathan1,*, Rao Darapu Narasimha1, Ignatious Joseph2, AswinDev Meleth Parambil2, Vivek Rachuri1, Behera Swarnaprava1, Balachandran Kizhakkepat Kalathil3
1CSIR – National Institute of Oceanography, Regional Centre, Visakhapatnam, India;
e-mail: jagadeesanl@nio.org
2School of Ocean Science and Technology, Kerala University of Fisheries and Ocean Studies, Panangad, India
3CSIR – National Institute of Oceanography, Regional Centre, Kochi, India
*corresponding author

keywords: River influx, Low saline plume advection, Mesoscale eddy, Chlorophyll a, Double chlorophyll maxima, Bay of Bengal

Received 2 February 2021, Revised 22 April 2021, Accepted 28 April 2021, Available online 20 May 2021.

Abstract

This study delineates the role of small and medium river inputs, Low Saline Plume Advection (LSPA) and eddies in hydrography alteration and Chlorophyll a (Chl. a) in the Western Bay of Bengal. Samples were collected across five transects viz: Hooghly (HO), Mahanadi (MN), Rushikulya (RK), Visakhapatnam (VSKP) and Godavari (GD) during Fall Intermonsoon. Each transect consists of 7 or 8 locations from inshore to offshore. LSPA propagates southward concordance with the East India Coastal Current (EICC) and its southward flow strengthened by a cold-core eddy. LSPA results in the intermittent low salinity in the cross-shore section of HO, MN and RK. Upper layer Chl. a is 2–3 folds higher in inshore and in LSP-influenced locations than in its adjacent stations. The present study identified Double Chlorophyll a Maxima (DoCM) in LSPA-influenced slope regions of MN and RK. DoCM is less known in the BoB. DoCM has both the Surface Chl. a Maxima (SCM) and Subsurface Chl. a Maxima (SSCM). SSCM layer is relatively shallow and intense in slope and offshore regions of MN and RK due to their closeness with cold-core eddy. The present study highlights that freshwater discharge from small and medium rivers impacts hydrobiology around 10–50 km from the shore depends on the magnitude of river influx. LSPA is away from the local inputs and impacts hydrobiology (>500 km) along the path. EICC and eddies together regulated the direction of LSPA. Existing eddies nature alters vertical hydrobiology in slope and offshore regions.
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Performance evaluation of non-water absorption coefficient partitioning algorithms in optically complex coastal waters of Kochi and Goa, India
Oceanologia 2021, 63(4), 420-437
https://doi.org/10.1016/j.oceano.2021.05.001

Srinivas Kolluru*, Shirishkumar S. Gedam, Arun B. Inamdarh
Centre of Studies in Resources Engineering, Indian Institute of Technology, Bombay, India;
e-mail: savinirs.milas@gmail.com
*corresponding author

keywords: Absorption, Phytoplankton, CDOM, Non-algal particulate matter, Partitioning algorithms

Received 13 September 2020, Revised 9 April 2021, Accepted 1 May 2021, Available online 24 May 2021.

Abstract

Absorption coefficient partitioning algorithms (APAs) were developed to partition the total absorption coefficient (a(λ)) or total non-water absorption coefficient (anw(λ)) into the absorption subcomponents, i.e., absorption due to phytoplankton aph(λ), colored dissolved organic matter (CDOM) ag(λ) and non-algal particulate matter ad(λ), λ is the wavelength. Absorption coefficients of CDOM and non-algal particulate matter are generally combined due to a similarity in exhibited spectral shape and represented as colored detrital matter (CDM) absorption coefficient, adg(λ). This study focuses on the applicability of five APAs Schofield's, Lin's, Zhang's, Stacked Constraints Model (SCM) and Generalized Stacked Constraints Model (GSCM), in deriving the absorption subcomponents from anw(λ)in optically complex coastal waters of Kochi and Goa, India. The average spectral Mean Absolute Percentage Errors (MAPE) obtained for all models in the retrieval of aph(λ), ad(λ), ag(λ) and adg(λ) lie in the ranges of 26–44%, 37–45%, 34–65% and 42–56%. Slopes of adg(λ), ag(λ) and ad(λ) as indicated by Sdg, Sg and Sdare derivable from GSCM, Schofield and Lin's models only. GSCM model exhibited good retrieval capability of Sd with MAPE values of 22% and a correlation coefficient of 0.74. In retrieval of parameter, none of the models demonstrated satisfactory performance. Overall, the GSCM and Schofield's models demonstrated good performance in the retrieval of absorption subcomponents, aph(λ), adg(λ), ad(λ) and Sd. Effect of applying baseline correction to ad(λ)on model performance is studied. Tuning with in situ data can further improve the absorption subcomponent and slope parameter retrieval capability of the models.
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Ocean Fronts detection over the Bay of Bengal using changepoint algorithms – A non-parametric approach
Oceanologia 2021, 63(4), 438-447
https://doi.org/10.1016/j.oceano.2021.05.003

Venkat Shesu Reddem1,*, Ravichandran Muthalagu2, Venkateswara Rao Bekkam3, Pattabhi Rama Rao Eluri1, Venkata Jampana1, Kumar Nimit1
1Indian National Centre for Ocean Information Services, Hyderabad, India;
e-mail: venkat@incois.gov.in
2National Centre for Polar and Ocean Research, Vasco-da-Gama, India
3Jawaharlal Nehru Technological University, Hyderabad, India
*corresponding author

keywords: Ocean fronts, Satellite imagery, Contextual median filter, Changepoint detection

Received 26 October 2020, Revised 30 April 2021, Accepted 12 May 2021, Available online 26 May 2021.

Abstract

Oceanic fronts are regions over the oceans where a significant change in the characteristics of the water masses is observed. Advanced Very High Resolution Radiometer (AVHRR) satellite imagery over the Bay of Bengal shows regions that are populated by frontal structures. Over the Bay of Bengal, some of the strongest gradients in temperature and salinity are observed. In recent years, there has been a tremendous growth in the availability of satellite imagery and the necessity of automated fast detection of the frontal features is needed for services like potential fishing zones over open oceans. In this article, an algorithm to infer oceanic fronts over the Bay of Bengal is described using changepoint analysis. The changepoint algorithm is combined in a novel way with a contextual median filter to detect frontal features in AVHRR imagery. The changepoint analysis is a non-parametric technique that does not put thresholds on the gradients of brightness temperatures of the satellite imagery. In the open oceans, the gradients of temperature and salinity are not sharp and changepoint analysis is found to be a useful complementary technique to the existing front detecting methods when combined with contextual median filters.
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Experimental study of hydraulic response of smooth submerged breakwaters to irregular wavesy
Oceanologia 2021, 63(4), 448-462
https://doi.org/10.1016/j.oceano.2021.05.002

Seyed Masoud Mahmoudof1,*, Fatemeh Hajivalie1,2
1Iranian National Institute for Oceanography and Atmospheric Sciences (INIOAS), Tehran, Iran;
e-mail: m_mahmoudof@inio.ac.ir
2Ghent University, Department of Civil Engineering, Technologiepark 60, 9052, Ghent, Belgium.
*corresponding author

keywords: Impermeable submerged breakwaters, Laboratory measurements, Transmission, Reflection, Dissipation

Received 7 March 2021, Revised 5 May 2021, Accepted 12 May 2021, Available online 27 May 2021.

Abstract

This paper presents the results of a laboratory experiment on transmission, reflection, and dissipation of irregular waves over smooth impermeable submerged breakwaters. Experiments included 75 JONSWAP-based irregular waves with five different wave characteristics generated at three water depths in a 2D wave flume. The investigated breakwater sections were three rectangular breakwaters with different widths, a toothed rectangular breakwater, and a trapezoidal breakwater with a slope of 1:2.
A new comprehensive dimensionless parameter (β) was proposed representing both wave hydrodynamic and breakwater geometry characteristics. This parameter could be employed as a suitable descriptive option to make an accurate estimate of the hydraulic performances of submerged breakwaters. The β parameter is composed of four conventional simple dimensionless variables. However, the results revealed that the relative submergence depth significantly affects the hydraulic responses of submerged breakwaters. The transmission, reflection and dissipation of waves show a logarithmic growth, a logarithmic reduction, and a quadratic decreasing trend against the increasing of β parameter, respectively. The verifications of results revealed the high efficiency of β parameter for data reported by Carevic et al. (2013) with R2 = 0.88 and high agreement with predictions made by Van der Meer et al. (2005) formulation with R2 = 0.93.
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Characterization of phytoplankton size-structure based productivity, pigment complexes (HPLC/CHEMTAX) and species composition in the Cochin estuary (southwest coast of India): special emphasis on diatoms
Oceanologia 2021, 63(4), 463-481
https://doi.org/10.1016/j.oceano.2021.05.004

Meenu Paul, Madhu Nikathithara Velappan*, Ullas Nanappan, Vineetha Gopinath, Rehitha Thekkendavida Velloth, Ashwini Rajendran, Maheswari Nair, Anil Peariya
CSIR – National Institute of Oceanography, Regional Centre, Kochi, India;
e-mail: nmadhu@nio.org
*corresponding author

keywords: Phytoplankton, Photopigments, Cochin estuary, Diatoms, Fucoxanthin

Received 5 February 2021, Revised 23 March 2021, Accepted 27 May 2021, Available online 16 June 2021.

Abstract

Seasonal studies on size-fractionated phytoplankton productivity (biomass and primary production), marker pigments, and species composition and abundance were carried out in the Cochin estuary (CE), located on the southwest coast of India, to identify the critical environmental factors that control the consistent preponderance of diatoms. The overall results of the study showed a significant contribution of small-sized phytoplankton, specifically nanophytoplankton (2–20 µm), to the total chlorophyll a and primary production in the estuary, regardless of seasons. Diatoms constituted the major phytoplankton taxa, showed an exceptional seasonal scale increase in numerical abundance during the post-southwest monsoon. The relative increase in fucoxanthin (biomarker of diatoms) over other marker pigments substantiated the numerical dominance of diatoms throughout the sampling periods. This is the first study in the CE in which phytoplankton marker pigments have been detected and elucidated the seasonality of functional groups based on HPLC/chemotaxonomy analytical approaches. The prevalence of high DiatDP and diatom chlorophyll a equivalent (estimated by CHEMTAX), further confirmed the preponderance of diatoms in the CE, despite the intermittent dominance of cyanophytes and cryptophytes (monsoon period). The consistent increase in SPM levels (> 25 mg L–1), established at all sampling stations, indicated that the water column turbidity might be one of the significant environmental factors hindering the growth of large-sized phytoplankton (ca. >20 µm) in the CE even if the system invariably holds high inorganic nutrients, irrespective of seasons.
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Spectral indexation of pixels of MODIS sea surface images for detecting inconstancy of phytopigment composition in water
Oceanologia 2021, 63(4), 482-496
https://doi.org/10.1016/j.oceano.2021.06.001

Genrik S. Karabashev*
Laboratory of ocean optics, Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia;
e-mail: genkar@mail.ru

keywords: MODIS, Baltic Sea, Gulf of Mexico, Spectral indexation, HABs, Phytopigments

Received 22 May 2020, Revised 31 May 2021, Accepted 11 June 2021, Available online 26 June 2021.

Abstract

This paper presents the first results of a new way of using MODIS (Moderate Resolution Imaging Spectroradiometer) sensor data to visualize phytopigment inconstancy in the near-surface layer of water basins. Other sensors of this class alike, the MODIS spectral resolution is too low to reproduce the minimums of reflectance Rrs caused by phytopigments in water. However, MODIS is remarkable for the presence of a channel at 469 nm combined with channels at 412, 443, 488, 531, 547, and 555 nm. This makes it possible to distinguish the spectral limits of preferential light absorption by chlorophyll a (412–469 nm) and by accessory pigments (469–555 nm). These capabilities were realized thanks to spectral pixel indexation (SPI) of MODIS images of the sea surface. The SPI boils down to the fact that a user determines the presence of pigment minima in spectra of every image pixel, finds the sum of the wavelengths of these minima as a WRM code and assigns it to the image pixel as one of its attributes. WRM code = 100 is assigned to pixels free of the minima. Such indexation makes it possible to examine the inconstancy of phytopigments on the background of aquatic environment variability. Application of SPI approach to MODIS images of the Gulf of Mexico and the Baltic Sea made it possible to reveal new patterns of phytopigment dynamics during HABs events.
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Validation and statistical analysis of the Group for High Resolution Sea Surface Temperature data in the Arabian Gulf
Oceanologia 2021, 63(4), 497-515
https://doi.org/10.1016/j.oceano.2021.07.001

Oleksandr Nesterov1,*, Marouane Temimi2, Ricardo Fonseca3, Narendra Reddy Nelli3, Yacine Addad1, Emmanuel Bosc4, Rachid Abida1
1Department of Nuclear Engineering, Emirates Nuclear Technology Center, Khalifa University of Science and Technology, UAE;
e-mail: oleksandr.nesterov@ku.ac.ae
2Department of Civil, Environmental, and Ocean Engineering (CEOE), Stevens Institute of Technology, Hoboken, NJ, USA
3ENGEOS Lab, Research Division, Khalifa University of Science and Technology, UAE
4Federal Authority for Nuclear Regulation, Abu Dhabi, UAE
* corresponding author

keywords: Arabian Gulf, Oman Sea, GHRSST, SST exceedance statistics, SST trends

Received 28 November 2020, Revised 4 June 2021, Accepted 5 July 2021, Available online 18 July 2021.

Abstract

The combined effect of climate change and steadily increasing seawater demand for industrial and domestic purposes in the Arabian Gulf region has a significant impact on the ecosystem in this region. Additionally, this effect may reduce the efficiency and increase the operating costs of industrial facilities that utilize seawater for cooling and other purposes. In this context, it is important to know various statistical characteristics of the sea surface temperature (SST) and their trends, in addition to the mean climatological characteristics. The analysis conducted in this study utilized a 17-year Group for High Resolution Sea Surface Temperature Level 4 dataset of 0.01 × 0.01° spatial resolution. First, the dataset was compared against a 2-year seawater temperature measurements at the ten offshore buoys in the relatively shallow coastal waters of the United Arab Emirates between Ras Ghumais and Dubai, which showed a reasonably good agreement between the two datasets, with the estimated root mean square deviations ranging from 0.5 to 0.9°C. Subsequently, several statistical SST characteristics were calculated. The trend analysis showed not only positive tendencies in the mean SSTs of up to 0.08°C/year in the northern Gulf, but also the trends in the annual percentile exceedances, particularly the 95th percentiles (near-maximum SSTs), which increased by approximately 0.07°C/year in the western United Arab Emirates and eastern Qatar waters. On the contrary, the 5th percentiles (near-minimum SSTs) decreased by up to 0.1°C/year, especially in the waters around Bahrain, Qatar, and the western United Arab Emirates. These results indicate that extreme hot and cold SST events in the Gulf are becoming more frequent and more extreme than before.
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A study on loops and eddies identified from the trajectories of drifters in the North Indian Ocean
Oceanologia 2021, 63(4), 516-530
https://doi.org/10.1016/j.oceano.2021.07.002

Shrikant Dora1,2, S.G. Aparna1,2,*
1CSIR –National Institute of Oceanography, Dona Paula, Goa, India;
e-mail: aparna@nio.org
2Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
*corresponding author

keywords: Drifters, Trajectories, Eddies, Arabian Sea, Bay of Bengal, North Indian Ocean

Received 23 October 2020, Revised 30 June 2021, Accepted 5 July 2021, Available online 19 July 2021.

Abstract

We identify loops and eddies from the trajectories of the drifters in the North Indian Ocean (NIO) from October 1985 to March 2019. We use the geometric identification method to identify loops and eddies and compare them with the loops identified from loopers provided by Lumpkin (2016). In NIO, the number of loops estimated from loopers is less than the number of loops and eddies identified by the geometric identification method. A total of 761 loops are identified, of which 346 are eddies, whereas the loops identified from loopers are only 149. Larger radii loops and eddies are observed in the western and central Bay of Bengal (BoB) and the southwestern part of the Arabian Sea (AS). Temporal variation of loops and eddies shows a peak during April–May in the AS and September–October in the BoB. In the BoB, the temporal variation of cyclonic eddies matches with the variation in chlorophyll.
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Machine learning methods applied to sea level predictions in the upper part of a tidal estuary
Oceanologia 2021, 63(4), 531-544
https://doi.org/10.1016/j.oceano.2021.07.003

Nicolas Guillou*, Georges Chapalain
Laboratoire de Génie Côtier et Environnement (LGCE), Cerema, Plouzané, France;
e-mail: nicolas.guillou@cerema.fr
*corresponding author

keywords: Multiple regression methods, Artificial neural network, Multilayer perceptron, Elorn, Landerneau, Western Brittany

Received 16 March 2021, Revised 8 July 2021, Accepted 8 July 2021, Available online 21 July 2021.

Abstract

Sea levels variations in the upper part of estuary are traditionally approached by relying on refined numerical simulations with high computational cost. As an alternative efficient and rapid solution, we assessed here the performances of two types of machine learning algorithms: (i) multiple regression methods based on linear and polynomial regression functions, and (ii) an artificial neural network, the multilayer perceptron. These algorithms were applied to three-year observations of sea levels maxima during high tides in the city of Landerneau, in the upper part of the Elorn estuary (western Brittany, France). Four input variables were considered in relation to tidal and coastal surge effects on sea level: the French tidal coefficient, the atmospheric pressure, the wind velocity and the river discharge. Whereas a part of these input variables derived from large-scale models with coarse spatial resolutions, the different algorithms showed good performances in this local environment, thus being able to capture sea level temporal variations at semi-diurnal and spring-neap time scales. Predictions improved furthermore the assessment of inundation events based so far on the exploitation of observations or numerical simulations in the downstream part of the estuary. Results obtained exhibited finally the weak influences of wind and river discharges on inundation events.
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