Title


Science and Technology Indonesia
e-ISSN:2580-4391 p-ISSN:2580-4405
Vol. 7, No. 1, January 2022

Research Paper

Vertical Chlorophyll-a Concentration Profiles Observed on The Western Coast of
Northern Sumatera During the 2017 Northeast Monsoon
Iskhaq Iskandar1*, Qurnia Wulan Sari2, Aan Johan Wahyudi3, Afdal3, Wijaya Mardiansyah1

1Department of Physics, Faculty of Mathematics and Natural Sciences, Sriwijaya University, Palembang 30662, Indonesia
2Department of Marine Science, Faculty of Fishery and Marine Science, Padjadjaran University, West Java 40600, Indonesia
3Research Center for Oceanography, Indonesian Isntitute of Science, Jakarta 14430, Indonesia
*Corresponding author: iskhaq@mipa.unsri.ac.id

Abstract
Subsurface chlorophyll-a (chl-a) concentration variability on Sumatera’s Northwestern coast is part of the phytoplankton biomass
thatsupportsandenrichestheregion’sfisheriessupplies. Duringthe2017northeastmonsoonseasonfrom25th November25to11th
December, the Ekspedisi Widya Nusantara (E-WIN) collected data from 16 stations. The finding demonstrates a rise in subsurface
chl-aconcentrationasyougetclosertothecoast. Furthermore, thedeepchl-amaximum(DCM)isonlyfoundoffshore, withdepths
between 30 to 50 m and chl-a concentrations of 0.07 to 0.25 mg.m−3. Surface chl-a concentrations near the coast were found to
be high, ranging from 0.2 to 0.25 mg.m−3.
Keywords
Deep Chlorophyll-a Maximum, E-WIN Cruise, MODIS Aqua, Surface Chlorophyll-a

Received: 20 September 2021, Accepted: 11 December 2021
https://doi.org/10.26554/sti.2022.7.1.36-40

1. INTRODUCTION

Located in the tropical Indian Ocean, the Northern Sumatera
region is subject to the monsoon system. It has been known
that the monsoon system can generate upwelling/downwelling
process along the coast. Monsoon systems are thought to play
a signi�cant impact in ocean circulation in this area, accord-
ing to previous research (Sari et al., 2018). The change of
ocean circulation as well as nutrient source could a�ect ma-
rine food chain and �sheries production. The concentration
of chlorophyll-a (chl-a) has been proposed as the best proxy
for phytoplankton biomass, making it valuable for the study
of primary production (Huot et al., 2007). It should be noted
that this study was conducted for the subtropical water with
warm temperature. The photosynthetic parameters and thus
primary productivity depend on the environmental variables.
The primary productivity response may di�er depending on
the geography. Surface chl-a, for example, accounts for around
51% of the entire variance in integrated primary output in the
Argentine seas (Lutz et al., 2010; Segura et al., 2013).

The MODIS satellite data in Northern Sumatera were used
to examine the geographical and temporal variations of the
surface chl-a (Sari et al., 2018). The results demonstrate that
in Northern Sumatera during the peak of boreal fall (boreal
summer), the surface chl-a is high (low). Furthermore, the

monsoon system and associated atmosphere-ocean interactions
in the tropical Paci�c, namely the El Niño-Southern Oscilla-
tion (ENSO), and in the tropical Indian Ocean, namely the
Indian Ocean Dipole (IOD), have a signi�cant impact on the
abundance of surface chl-a (Sari et al., 2018; Siswanto et al.,
2015).

Chl-a maximum is not usually found at the sea surface, but
it can also be found deeper than the euphotic zone’s bottom.
The chl-a maximum cannot be measured using satellite remote
sensing in this circumstance. Moreover, seasonal and annual
variations of surface chl-a represent unique spatial patterns
on a global scale, according to satellite ocean color studies.
On regional scales, satellite ocean color studies indicated a
strong annual cycle of surface chl-a in the southeastern tropical
Indian Ocean and Northern Sumatera, resembling subtropical
or temperate regions (Susanto et al., 2006; Siswanto et al.,
2017; Iskandar et al., 2009; Amri et al., 2014; Sari et al.,
2018).

In this paper, we used vertically observed chl-a concentra-
tion from the E-WIN cruise during early of the 2017 northeast
monsoon season in the western coast of Northern Sumatera
region. The goal of this research is to look at the vertical pat-
terns of chl-a concentration along the cruise track in Sumatera’s
Northern portion. The rest of the paper is laid out as follows.
The study area, data, and techniques are all described in Section

https://crossmark.crossref.org/dialog/?doi=10.26554/sti.2022.7.1.36-40&domain=pdf
https://doi.org/10.26554/sti.2022.7.1.36-40


Iskandar et. al. Science and Technology Indonesia, 7 (2022) 36-40

2. In Section 3, we describe and discuss the study’s primary
�ndings. The study’s result is presented in the �nal part.

2. EXPERIMENTAL SECTION

2.1 Materials
The research area is located between 12°N - 3°S and 90°E -
102°E on the western coast of northern part of Sumatera (Fig-
ure 1). The E-WIN cruise was conducted from 25 November
to 11 December 2017 using the RV. Baruna Jaya VIII of the
Indonesian Institute of Sciences. The cruise started from the
station E1 near Sabang, Aceh to the station E16 in the eastern
Simeuleu Island (Figure 1). The cruise tracks are indicated by
red line, while the Conductivity-Temperature-Depth (CTD)
observation stations are indicated by yellow �lled-stars.

Figure 1. The Transect of The E-WIN Expedition During The
Northeast Monsoon of 2017 Is Shown by The Red Line, and
The CTD Stations Are Indicated by The Yellow Filled-Circle.

2.2 Methods
Chl-a concentrations were sampled at 16 locations along North-
ern Sumatera’s western coast. With a Rosette sampler from
Niskin Bottles installed on a Sea-Bird Electronics conductivity-
temperature-depth (CTD) type SBE-911 plus, discrete sea-
water samples were taken from 6 �xed depths (5, 50, 75, 100,
150, and 300 m) at each station. Measurements of nutrient
concentrations (phosphate, nitrate, and silicate) were carried
out using the HACH spectrophotometer (Suzuki et al., 1995).
The �uorometric approach was used to measure phytoplankton
chl-a concentrations, as recommended by U.S. Environmen-
tal Protection Agency (1983). Under a vacuum pump with
a pressure less than 30 cmHg, 0.1-1.0 liter of water was �l-
tered using the Whatman CNM porous �lter with a 0.45 m
and 25 mm diameter. Before being examined, the membrane
�lters were stored in a cooler (with temperatures below 4°C) for
roughly 20 hours after being wrapped in aluminum foil (U.S.
Environmental Protection Agency , 1983). After �ltration, the
samples were extracted using a 90 percent acetone extraction
solution (Cochlan and Hendorn, 2012; Holm-Hansen et al.,
1965) and centrifuged for 30 minutes at 4,000 rpm to sep-
arate the �lter from the chl-a-containing solution (Cochlan

and Hendorn, 2012; Holm-Hansen et al., 1965). The vertical
pro�les of �uorescence are then obtained by reading the �uo-
rescent liquid using the AU-10 Turner Trilogy Fluorometer.
The concentration of phytoplankton chl-a is de�ned as,

Chl-a(`g/L) = ((y −b)/m)(v/V ) (1)

where y is a �uorescence value, b is the y axis value that
intersects the curve calibration, m is a slope of the regression line
on the standard curve (calibration), v is a volume of the extract
(after addition of acetone 90%) (mL), and V is the volume of
�ltered sample (mL).

Using CTD dataset, the mixed layer depth (MLD) was
calculated as a depth where the density increases by 0.125
kg.m−3 from that of the reference point (10 m deep) Zeng and
Wang (2017) as shown in Table 1.

Table 1. Calculated Mixed Layer Depth using Density Criterion

Station MLD (m)

E017-01 31
E017-02 20
E017-03 21
E017-04 15
E017-05 20
E017-06 25
E017-07 14
E017-08 50
E017-09 25
E017-10 22
E017-11 31
E017-12 18
E017-13 23
E017-14 24
E017-15 12
E017-16 19
E017-17 31

The in situ data is also compared to the surface chl-a con-
centration remotely-sensed by the Moderate Resolution Imag-
ing Spectroradiometer (MODIS) aboard the Aqua satellite be-
tween 25th November and 18th December 2017. The NASA
Goddard Distributed Active Archive Center provided the satel-
lite data, which had a horizontal resolution of 4 km (https://modi
s.gsfc.nasa.gov/).

3. RESULTS AND DISCUSSION

3.1 Vetical Pro�les of Chlorphyll-a Concentrations and Flu-
orescences

Based on the distance of stations to the coast, the water char-
acteristics of the western coast of Northern Sumatera can be
clustered into two regions (Figure 1), namely the o�shore and
the coastal waters. The vertical pro�les of chl-a along the west-
ern coast of Northern Sumatera, along with the vertical pro�les

© 2022 The Authors. Page 37 of 40



Iskandar et. al. Science and Technology Indonesia, 7 (2022) 36-40

of the observed �uorescene, were used to identify each obser-
vation station in the present study. The �uorescene can be
employed as an indicator of chl-a concentration, according
to the method proposed in early study (Sauzède et al., 2015;
Zhao et al., 2019). The water characteristic with deep chl-a
maximum (DCM) and high surface chl-a (HSC) pro�le data
was used to characterize the chl-a visual analysis (Lavigne et al.,
2015). Vertical chl-a pro�les are often described using the
DCM and HSC forms (Lavigne et al., 2015). They are char-
acterized by the relative position of MLD and are referred to
as "strati�ed" and "mixed," respectively. The HSC standard
shape was generated for pro�les with a continuous decrease
in chl-a from surface to depth (approximately 100 m), such
as those seen during phytoplankton blooms (Chiswell, 2011).
Pro�les with relatively high values in the mixed layer and a
�uoresence peak directly below the MLD are represnted by the
DCM form. Table 1 shows that the MLD in the study area was
usually between 14 and 50 m. The deepest MLD is at station
E017-08, with a depth of 50 m, while the shallowest MLD is
at station E017-17, with a depth of 14 m.

Figure 2. Vertical Pro�les of (a, d) Chl-a Concentration, (b, e)
Fluorescence, and (c, f) Turbidity. The Classi�cation is Based
on Avertical Chl-a Concentration Pro�le, with The Upper
Panel Representing Stations with High Surface Chl-a (HSC),
and The Lower Panel Representing The Stations with Deep
Chl-a Maximum (DCM)

Figure 2 depicts chl-a concentration, �uorescence, and tur-
bidity pro�les in Northern Sumatera waters from the surface
to 300 m depth. Figures 2a and 2d show that the observed
pro�les of chl-a concentration are remarkably comparable to
the pro�les of �uorescence (Figures 2b and 2e). With the ex-
ception of station E017-05, where no chl-a was identi�ed in
the surface water, the surface chl-a concentration in Northern
Sumatera waters was about 0.051 to 0.21 mg.m−3 (Figures 2a
and 2d). This indicates that the Northern Sumatera waters are
oligotrophic waters. The high and low concentration of chl-a
is closely related to the supply of nutrients originating from
the land through the rivers discharge into these areas. The sur-

face chl-a concentration was found more at the stations located
close to the land than that at the stations located toward the sea.
The highest concentration of surface chl-a was found at station
E017-13, which lies between the Sumatera and Simelue Island
with a value of 0.21 mg.m−3. In the east of Simelue Island,
we found turbid waters caused by the presence of suspended
particles and high levels of sludge which were carried from
the land and rivers around the island. Meanwhile, the lowest
concentration of surface chl-a was observed at stations E017-
03 and E017-07. This is presumably because the location of
those stations were heading towards the open sea resulting in
little input of nutrients from the land which causes less surface
chlorophyll content.

It was con�rmed by Figure 2 that the stations located near
the coast are having high surface chl-a concentration, while
those located o�shore tend to have deep chl-a maximum. More-
over, the coastal water is also characterized by high turbid water
(Figure 2c). It is worth noting that the land gives a lot of in-
put into the waters. As a result, waters near the land become
fertile water which will ultimately be bene�cial for phytoplank-
ton to carry out photosynthetic activity. Previous study has
suggested that river runo� signi�cantly a�ect the content of
nutrients (Phosphate, Nitrate and Silicate) in the ocean (Zhang
et al., 2020). In addition, it can inferred aslo from Figures
2 that high chl-a concentrations are found at the stations lo-
cated around the estuary (stations E017-11 and E017-17).
The degree of acidity (pH) and nitrate play vital roles in the
aquatic environment’s health. pH �uctuations have an impact
on chemical processes and biological organisms in the water as
well as the toxicity of a chemical compound in water. The pH
of water has a signi�cant impact on its metabolic activities, for
example, if the pH is too low, nitri�cation will cease (Le et al.,
2019). While nitrate is a key component of primary produc-
tivity, it is also consumed by phytoplankton and is required for
photosynthesis (Li et al., 2010).

Figure 3. Same as Figure 2 Except for Vertical Pro�les of (a, d)
Phosphate, (b, e) Nitrate, and (c, f) Silicate.

Phosphate, nitrate, and silicate vertical pro�les are shown in

© 2022 The Authors. Page 38 of 40



Iskandar et. al. Science and Technology Indonesia, 7 (2022) 36-40

Figure 3. Phosphate has a vertical pro�le that ranges from 0.01
mg.m−3 at the surface to 0.063 mg.m−3 at 300 m depth (Fig-
ures 3a, d), while nitrate has a vertical pro�le that ranges from
0 near the surface to 0.49 mg.m−3 at 300 m depth (Figures 3a,
d) (Figures 3b, e). Silicate has a vertical pro�le ranging from
0.05 mg.m−3 near the surface to 0.57 mg.m−3 at 300 m under-
ground (Figures 3c, f). There was no discernible di�erence in
the vertical pro�les of phosphate, nitrate, and silicate between
the stations along the coast and those o�shore, according to
our �ndings.

3.2 The Weekly Satellite Surface Chl-a Distributions
We showed the distribution of surface chl-a before, during, and
after sampling in this study. Due to cloud cover, satellite image
quality was poor from 25th November to 2nd December 2017.
The satellite measurement nicely recorded the surface chl-a
concentration during the sample (December 3–10, 2017) and
after the sampling (December 11–18, 2017) (Figure 4). The
concentration of surface chl-a near the coast (0.3 – 1 mg.m−3)
is clearly higher than in the o�shore area (0.10 – 0.2 mg.m−3),
which is consistent with our in-situ observation.

Figure 4. Weekly Composite of Surface Chl-a Derived from
MODIS During a) 25 November-03 December 2017, b)
03-10 December 2017 and, c) 10-18 December 2017.

4. CONCLUSIONS

Based on in-situ observations obtained during the E-WIN
cruise from 25th November to 11th December 2017, this study
analyzed the vertical pro�le of chl-a concentration in North-
western Sumatera. Discrete seawater samples were taken at
depths ranging from 5 to 300 m. Note that while the HACH
spectrophotometer was used to assess nutrient concentrations
(phosphate, nitrate, and silicate), the �uorometric technique
was used to detect phytoplankton chl-a concentrations.

The results reveal geographical di�erences in vertical chl-a
concentrations, with high surface chl-a concentrations found
near the shoreline and DCM detected o�shore. Station E017-
13, located between Sumatera and Simelue Island, had the
highest surface chl-a concentration of 0.21 mg.m−3. The low-
est surface chl-a concentrations, on the other hand, were found
at open-sea stations E03 and E017-07. Furthermore, the stael-
lite pictures con�rmed that chl-a concentrations in the coastal
zone range from 0.30 to 1 mg.m−3, which is higher than the
0.10 to 0.2 mg.m−3 seen o�shore. The vertical pro�les of
phosphate, nitrate, and silicate showed no substantial regional
variation.

5. ACKNOWLEDGEMENT

The authors thank to the Indonesian Institutes of Sciences
(LIPI) through EWIN cruise 2017. This study is supported by
the Ministry of Education, Culture, Research and Technology,
Indonesia through the Penelitian dasar Unggulan Perguruan
Tinggi (PDUPT) 2021 (Contract Number: 150/E4.1/AK.04.P
T/2021). The third author (AJW) is supported by the LIPI-
JSPS Joint Research Grant (JPJSBP120198201) entitled In-
dian Ocean variability and its impact on climate and ecosystems
of the maritime continent (2019–2022).

REFERENCES

Amri, K., A. Priatna, and S. Suprapto (2014). Oceanographic
characteristics and abundance of phytoplankton in the waters
of the Sunda Strait in the east monsoon. Bawal Widya Riset
Perikanan Tangkap, 6(1); 11–20

Chiswell, S. M. (2011). Annual cycles and spring blooms in
phytoplankton: don’t abandon Sverdrup completely. Marine
Ecology Progress Series, 443; 39–50

Cochlan, W. and J. Hendorn (2012). Water quality methods.
Tiburon: Romberg Tiburon Center for Environmental Stud-
ies, San Fransisco State University; 317.

Holm-Hansen, O., C. J. Lorenzen, R. W. Holmes, and J. D.
Strickland (1965). Fluorometric determination of chloro-
phyll. Journal of Marine Science, 30(1); 3–15

Huot, Y., M. Babin, F. Bruyant, C. Grob, M. Twardowski, and
H. Claustre (2007). Does chlorophyll a provide the best
index of phytoplankton biomass for primary productivity
studies Biogeosciences Discussions, 4(2); 707–745

Iskandar, I., S. Rao, and T. Tozuka (2009). Chlorophyll-a
bloom along the southern coasts of Java and Sumatra during

© 2022 The Authors. Page 39 of 40



Iskandar et. al. Science and Technology Indonesia, 7 (2022) 36-40

2006. International Journal of Remote Sensing, 30(3); 663–
671

Lavigne, H., F. D’ortenzio, M. Ribera D’Alcalà, H. Claustre,
R. Sauzède, and M. Gacic (2015). On the vertical distribu-
tion of the chlorophyll a concentration in the Mediterranean
Sea: a basin-scale and seasonal approach. Biogeosciences,
12(16); 5021–5039

Le, T. T. H., J. Fettig, and G. Meon (2019). Kinetics and
simulation of nitri�cation at various pH values of a polluted
river in the tropics. Ecohydrology & Hydrobiology, 19(1);
54–65

Li, W. K., M. R. Lewis, and W. G. Harrison (2010). Multi-
scalarity of the nutrient–chlorophyll relationship in coastal
phytoplankton. Estuaries and Coasts, 33(2); 440–447

Lutz, V. A., V. Segura, A. I. Dogliotti, D. A. Gagliardini, A. A.
Bianchi, and C. F. Balestrini (2010). Primary production
in the Argentine Sea during spring estimated by �eld and
satellite models. Journal of Plankton Research, 32(2); 181–
195

Kumar, S. P, M. Nuncio, J. Narvekar, (2004). Are eddies
nature’s trigger to enhance biological productivity in the Bay
of Bengal Geophysical Research Letters, 31(7); 1-8

Sari, Q. W., P. A. Utari, D. Setiabudidaya, I. Yustian,
E. Siswanto, and I. Iskandar (2018). Variability of sur-
face chlorophyll-a distributions in the northwestern coast of
Sumatra revealed by MODIS. In Journal of Physics: Confer-
ence Series, 1080; 012045

Sauzède, R., H. Lavigne., H. Claustre., J. Uitz., C. Schmechtig.,
F. d’Ortenzio., C. Guinet, and S. Pesant (2015). Vertical dis-
tribution of chlorophyll a concentration and phytoplankton
community composition from in situ �uorescence pro�les: a
�rst database for the global ocean. Earth System Science Data,
7(2); 261–273

Segura, V., V. A. Lutz, A. Dogliotti, R. I. Silva, R. M. Negri,

R. Akselman, and H. Benavides (2013). Phytoplankton
types and primary production in the Argentine Sea. Marine
Ecology Progress Series, 491; 15–31

Siswanto, E., K. Matsumoto, M. C. Honda, T. Fujiki,
K. Sasaoka, and T. Saino (2015). Reappraisal of meridional
di�erences of factors controlling phytoplankton biomass and
initial increase preceding seasonal bloom in the northwestern
Paci�c Ocean. Remote Sensing of Environment, 159; 44–56

Siswanto, E., H. Ye, D. Yamazaki, and D. Tang (2017). De-
tailed spatiotemporal impacts of El Niño on phytoplankton
biomass in the S outh C hina S ea. Journal of Geophysical
Research: Oceans, 122(4); 2709–2723

Susanto, R.D., Moore, T.S. and Marra, J (2006). Ocean color
variability in the Indonesian Seas during the Sea WiFS era.
Geochemistry, Geophysics, Geosystems, 7(5); 1-10

Suzuki, K., N. Handa, H. Kiyosawa, and J. Ishizaka (1995).
Distribution of the prochlorophyte Prochlorococcus in the
central Paci�c Ocean as measured by HPLC. Limnology and
Oceanography, 40(5); 983–989

U.S. Environmental Protection Agency (1983). Methods for
Chemical Analysis of Water and Wastes. EPA-600/4-79-020:
Washington

Zeng, L. and D. Wang (2017). Seasonal variations in the barrier
layer in the South China Sea: characteristics, mechanisms
and impact of warming. Climate Dynamics, 48(5-6); 1911–
1930

Zhang, P., J.-L. Xu, J.-B. Zhang, J.-X. Li, Y.-C. Zhang, Y. Li,
and X.-Q. Luo (2020). Spatiotemporal Dissolved Silicate
Variation, Sources, and Behavior in the Eutrophic Zhanjiang
Bay, China. Water, 12(12); 3586

Zhao, C., J. Maerz, R. Hofmeister, R. Röttgers, K. Wirtz,
R. Riethmüller, and C. Schrum (2019). Characterizing the
vertical distribution of chlorophyll a in the German Bight.
Continental Shelf Research, 175; 127–146

© 2022 The Authors. Page 40 of 40


	INTRODUCTION
	EXPERIMENTAL SECTION
	Materials
	Methods

	RESULTS AND DISCUSSION
	Vetical Profiles of Chlorphyll-a Concentrations and Fluorescences 
	The Weekly Satellite Surface Chl-a Distributions

	CONCLUSIONS
	ACKNOWLEDGEMENT