Journal of Oceanography
https://doi.org/10.1007/s10872-021-00616-3

SPECIAL SECTION: ORIGINAL ARTICLE
Coastal Ecosystem Change in Asia: Hypoxia, Eutrophication, and Nutrient Conditions

Hypoxia in the Upper Gulf of Thailand: Hydrographic observations
and modeling
Akihiko Morimoto1 · Yoshihisa Mino2 · Anukul Buranapratheprat3 · Atsushi Kaneda4 · Siraporn Tong‑U‑Dom3 ·Kalanyu Sunthawanic5 · Xiaojie Yu6 · Xinyu Guo1
Received: 3 April 2021 / Revised: 29 July 2021 / Accepted: 12 August 2021
© The Oceanographic Society of Japan and Springer Nature Singapore Pte Ltd. 2021

Abstract
We conducted hydrographic observations throughout the year to investigate seasonal variations of the hypoxic water mass
distribution in the Upper Gulf of Thailand (UGoT). Hypoxic water masses were observed from June to November, with halfof the UGoT occupied by hypoxic water in September. A hypoxic water mass appeared in the northeastern part of the UGoTin June and August, and moved westward over time. Low-salinity surface water moved from east to west as the rotational
direction of surface circulation shifted with the reversal of monsoon winds. Westward movement of low-salinity water causes
strong stratification in the northwestern part of the UGoT, leading to severe hypoxia. Numerical experiments showed highdissolved oxygen consumption rates around and offshore of river mouths, where hypoxic water is generated. This finding
suggests that hypoxic water masses are transported to the south by physical processes. We examined how flooding affects
hypoxic water mass formation. The volume of hypoxia in a flood year was approximately 2.5 times greater than in a normal
year. In addition, hypoxia occurred in the dry season and extensive hypoxia was observed in the year after flooding. These
results suggest that the hypoxic water mass persists for a long time after flooding.
Keywords Hypoxia · Upper Gulf of Thailand · Ecosystem model

1 Introduction
Hypoxia, which is often defined as a dissolved oxygen (DO)concentration in seawater of less than 2 mg ­l−1 (Diaz 2001;
Kemp et al. 2009) has occurred since the 1960s in the costal* Akihiko Morimoto
morimoto.akihiko.cl@ehime-u.ac.jp
1

Center for Marine Environmental Studies, Ehime University,
2‑5 Bunkyo‑Cho, Matsuyama, Ehime 790‑8577, Japan

2

Institute for Space-Earth Environmental Research, Nagoya
University, Nagoya, Aichi, Japan3

Department of Aquatic Science, Faculty of Science, Burapha
University, Chonburi, Thailand

4

Faculty of Marine Science and Technology, Fukui Prefectural
University, Obama, Fukui, Japan

5

Department of Mathematics, Faculty of Science, Mahidol
University, Bangkok, Thailand

6

Key Laboratory of Marine Environment and Ecology, Mistryof Education, Ocean University China, Qingdao, China

seas of developed countries such as the United States andJapan, and in European countries, due to enormous nutrientand organic matter inputs via rivers in association with rapid
economic growth (Diaz 2001; Capet et al. 2013; Carstensen
et al. 2014; Li et al. 2016; Breitburg et al. 2018; Rabalais
and Turner 2019). Although substantial efforts have been
made over time to reduce hypoxia in many countries, theenvironmental problem of hypoxia has not yet been solved(Diaz and Rosenberg 2008; Kemp et al. 2009). For example,
after an eutrophication problem arose in the Seto Inland Sea
in Japan, sewage systems were installed and total volume
control was applied for nitrogen and phosphorus. As a result,nutrient concentrations in the Seto Inland Sea decreased.
However, hypoxia continued to occur every summer inOsaka Bay, which is located in the eastern part of the Seto
Inland Sea (Nakajima and Fujiwara 2007). Only Dokai Bay
in Japan, which is a very narrow and small embayment,
showed improvement from hypoxic conditions (Yanagi and
Yamada 2014). These findings demonstrate that it is difficult
for the marine environment to recover from hypoxic conditions. Recently, hypoxia has also occurred in developing

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A. Morimoto et al.

countries in Southeast Asia due to rapid economic growth(e.g., Jacinto et al. 2011; Sotto et al. 2014; Hayami et al.
2020). Hypoxia has become a worldwide environmental
problem affecting coastal seas. However, reports of hypoxia
in Southeast Asia are scarce, likely due to a lack of observed
data. In terms of hypoxia, coastal marine environments inSoutheast Asia might be more severely impacted than firstthought. Tropical regions might be more vulnerable tohypoxia than temperate regions because the solubility ofoxygen is lower due to higher water temperatures throughout the year (Altieri and Gedan 2015), and because verticalmixing is weaker due to a lack of winter cooling. In addition,
during the rainy season, a large amount of fresh water withhigh nutrient levels flows into coastal seas, leading to strong
density stratification (Buranapratheprat et al. 2008a) that inturn might lead to red tides and hypoxia (Lirdwitayaprasit
et al. 2006; Buranapratheprat et al. 2009).
The Upper Gulf of Thailand (UGoT) borders the capital city of Thailand (Bangkok). The width and length of
the UGoT are approximately 100 km, and the UGoT is avery shallow bay with a maximum water depth of less than
40 m. Five rivers, the Bangpakong, Chaopraya, Thachin,
Maeklong, and Phet Chaburi, supply fresh water and materials such as nutrients and organic matter to the UGoT
(Fig. 1). The largest river is the Chaopraya River (mean discharge of 718 ­m3 ­s−1), which passes through Bangkok city.
Although the UGoT is a high-productivity coastal sea withhigh fish production, the marine environment of the UGoT

has recently deteriorated due to large inputs of organic andinorganic matter from its five inflowing rivers. Mass mortality of shellfish and fish occurs every year from August
to early October along the eastern coast of the UGoT. This
mortality might be due to red tides and hypoxia. Morimoto
et al. (2013) reported that hypoxia and anoxia occurred in
the river mouth area of the Bangpakong River from late September to October. In addition, they suggested that a watermass with low DO was transported from another area to the
Bangpakong River estuary, indicating that hypoxia occurs
over a large area of the UGoT. Chongprasith and Srineth(1998) and Cheevaporn and Menasveta (2003) both reported
eutrophication throughout the entire UGoT. Massive quantities of nutrients from rivers comparing to those in developed
countries are transported along the UGoT coast via a clockwise circulation pattern in summer and an anti-clockwise
pattern in winter (Buranapratheprat et al. 2002). The northern part of the UGoT has a content of high chlorophyll-a,which moves westward or eastward according to the season(Buranapratheprat et al. 2008a, b). It has been suggested thathypoxia or anoxia occur across large areas of the UGoT, but
few data show the seasonal variations of DO concentration
across the whole UGoT.
In the present study, we reveal seasonal variations of
DO concentration across the entire UGoT based on hydrographic observations, and investigate the factors that generate hypoxia. Then, we describe a coupled physical-ecosystem model developed to clarify the spatial and temporal

Fig. 1  Bathymetry in the Upper Gulf of Thailand. Black dots denotehydrographic observation stations and red stars denote observation
point in the rivers. Temporal variations in DO, DO consumption

rate, PON concentration, vertical integrated chlorophyll-a and intensity of stratification shown in Figs. 11, 12, and 13 are examined inthree red square areas (colour figure online)

13

Hypoxia in the Upper Gulf of Thailand: Hydrographic observations and modeling﻿	variations of hypoxia in the UGoT. In addition, we examine
the influence of river discharge changes on the volume andhorizontal distribution of the hypoxic water mass, as flooding occurs in some years and river discharge has shown arecent increasing trend.

2 Observations and numerical modeling
2.1 Hydrographic observations
We conducted seven sets of hydrographic observations,from August 2014 to June 2015, by the research vessel ofKasetsart University. Dates of the observations and moonphase are shown in Table 1. We sampled 18 stations in the
UGoT (Fig. 1), using a RINKO Profiler (JFE Advantec Co.
Ltd.) for measurement of water temperature, salinity, DO,fluorescence, and turbidity. The vertical interval of the data
was 0.1 m at each station. We collected water samples 1 m
below the sea surface and 1 m above the bottom for measurement of DO, chlorophyll-a, and nutrient concentrations(nitrate, nitrite, ammonia, phosphate, and silicate). The DOconcentrations of water samples were measured using the
Winkler method. Water samples for chlorophyll-a measurement were filtered onto 40-mm Whatman GF/F filters andthen immersed in N,N-dimethylformamide for extraction.
The chlorophyll-a concentration was analyzed with a Turner
Designs Model 10 fluorometer. DO and fluorescence values
measured with the RINKO Profiler were corrected according to the measured values of DO and chlorophyll-a derived
from water samples, respectively. The same types of observations were conducted at the mouths of five rivers (Fig. 1)
a few days before each hydrographic observation, as shownin Table 1. We collected water samples at 1 m below thesurface and 1 m above the bottom for measurement of DO,
chlorophyll-a, and nutrient concentrations in river water.

2.2 Physical and ecosystem numerical models
To reproduce physical properties such as current, watertemperature, and salinity during the observation period
Table 1  Observation days and moon phase of observed day

1
2
3
4
5
6
7

Observation date

Moon phase

August 8–10, 2014
September 22–24, 2014
November 5–7, 2014
December 18–20, 2014
February 16–18, 2015
April 2–4, 2015
June 14–16, 2015

12.2–14.2
27.5–29.5
12.2–14.2
25.6–27.6
26.6–28.6
12.7–14.7
26.9–28.9

from August 2014 to June 2015, we developed a threedimensional sigma-coordinate physical model based on the
Princeton Ocean Model (Blumberg and Mellor 1987; Mellor2003). The vertical and horizontal diffusivities are calculated with the momentum turbulent closure scheme (Mellor
and Yamada 1982) and Smagorinsky formula (Smagorinsky 1963), respectively. The horizontal and vertical resolutions of the model are 1/120 degree latitude and longitude,
and 10 sigma layers, respectively. The model domain is
99.75–101.25 E and 12.60–13.6 N (Fig. 1). The integration
period of the model is from January 1, 2014, to June 30,
2015. The model configurations are similar to those reported
by Yu et al. (2018), but the boundary conditions differ asfollows. Sea-level variation is enforced at the southern endof the model domain to reproduce tides and tidal currents.
We consider four main tidal constituents: ­M2, ­S2, ­O1, and­K1. The harmonic constants of these four tidal constituentsare determined at Sattahip and Hua Hin tide gauge stations,which are located in the southern part of the UGoT (Fig. 1),
and the harmonic constants were linearly interpolated into
grids with the southern end of the domain treated as an open
boundary condition. Daily wind stresses during the integration period were applied at the sea surface and calculated
from wind data observed at three stations around the UGoT.
Daily net heat flux obtained from the National Center for
Environmental Prediction (NCEP) from January 2014 toJune 2015 was used as a sea surface boundary condition.
We considered river discharge from five rivers, namely the
Bangpakong, Chaopraya, Thachin, Maeklong, and Phet
Chaburi. Monthly averaged river discharge data during the
integration period were used (Fig. 4). Vertical profiles ofwater temperature, salinity, and the north–south componentof the monthly mean current were set at the southern end of
the model domain as open boundary conditions, using values
derived from the diagnostic model results of Tong-U-Dom
et al. (2017).
We coupled the physical model described above with asimple ecosystem model to investigate the hypoxia in the
UGoT. The ecosystem model is a nutrient-phytoplanktonzooplankton-detritus (NPZD) model (e.g., Onitsuka et al.
2007; Buranapratheprat et al. 2008a, b) with DO processes
added (Kim et al. 2019) (Fig. 2). Variables in the model
include nutrients, dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), phytoplankton, zooplankton, detritus, and DO. Details of the NPZD model,such as its governing equations, were provided by Onitsuka
et al. (2007) and Kim et al. (2019), and the biogeochemical parameters of the NPZD model applied here are shownin Table 2. As lateral boundary conditions, DIN, DIP,
chlorophyll-a, and detritus were supplied from five rivermouths and an open boundary at the southern end of themodel domain based on observed concentrations. However,no detritus data were available. Therefore, we assumed that13

A. Morimoto et al.

Fig. 2  Configuration of ecosystem model

Table 2  Biogeochemicalparameters in the ecosystem
model

13

Definition

Value

Unit

Maximum photosynthetic rate of phytoplankton at 0 ℃
Half saturation constant of phytoplankton for DIN
Half saturation constant of phytoplankton for DIP
Temperature coefficient for the photosynthetic rate
Optimum light intensity for phytoplankton
Light dissipation coefficient of seawater
Self-shading coefficient
Respiration rate of phytoplankton at 0 ℃
Temperature coefficient for respiration
Mortality rate of phytoplankton at 0 ℃
Temperature coefficient for phytoplankton mortality
Maximum grazing rate of zooplankton at 0 ℃
Ivelev constantThreshold value for grazing
Temperature coefficient for grazing
Assimilation efficiency of zooplankton
Growth efficiency of zooplankton
Zooplankton mortality rate at 0℃
Temperature coefficient for zooplankton mortality
Decomposition rate of detritus at 0 ℃
Temperature coefficient of detritus for decomposition
Sinking velocity of detritus
Ratio of carbon to chlorophyll-a
Redfield ratio of C:N:P

0.75
3
0.1
0.0693
80
0.04
0.054
0.05
0.05190.03
0.0693
0.5
1.4
0.043
0.06930.7
0.3
0.06
0.06930.08
0.0693
1.5
50
106:16:1

day−1mmol N ­m−3mmol N ­m−3℃−1
W ­m−2m−1
m2 mmol ­N−1
day−1
℃−1
m3 mmol ­N−1 ­day−1
℃−1
day−1
m3 mmol ­N−1℃−1℃−1

m3 mmol ­N−1 ­day−1
℃−1
day−1
℃−1
m ­day−1

Hypoxia in the Upper Gulf of Thailand: Hydrographic observations and modeling﻿	

the concentration of detritus is 20% of the chlorophyll-aconcentration.

3 Results
3.1 Seasonal variations in observed bottom DO,
surface salinity, and surface chlorophyll‑a
Horizontal distributions of observed DO concentration at
1 m above the bottom, surface salinity, and surface chlorophyll-a at seven hydrographic observation time points from
August 2014 to June 2015 are shown in Fig. 3. We did notplot water temperature because the horizontal gradient ofwater temperature is small and vertically homogeneous ateach station throughout the year. Monthly river discharges
from each of the five rivers and total discharge are shownin Fig. 4. In the present study, a DO concentration less than
2 mg ­l−1 is defined as hypoxia, with reference to Diaz (2001)
and Kemp et al. (2009).
Hypoxia (< 2 mg ­l−1) occurred in the bottom layer offshore of the mouth of the Chaopraya River in August 2014.
The minimum DO value was 1.2 mg ­l−1 at station 2. Surface
salinity less than 31.0 psu occurred in the northeastern partof the UGoT, offshore of the Bangpakong and Chaopraya
rivers. Discharge of the Bangpakong and Chaopraya rivers
increased at the start of the rainy season. Although dischargeof the Chaopraya River was twice as high as that of the
Bangpakong River, the lowest salinity was observed off the
Bangpakong River mouth. This suggests that freshwater supplied from the Chaopraya River is transported eastward by
surface currents. Surface chlorophyll-a was nearly constant,
at approximately 1 mg ­m−3, across the whole UGoT.
In September 2014, a hypoxic water mass occupied halfof the total area of the UGoT, and the DO concentration wasless than 1 mg ­l−1 off the mouth of the Chaopraya River;anoxic water with a DO concentration of zero was observed
at station 3. Surface salinity became lower than in August.
The lowest salinity was observed in the northeastern part of
the UGoT, as in August. The surface salinities at stations 1
and 2 were 20.5 and 20.9 psu, respectively. A water massof more than 32.0 psu was present at the bay mouth of the
UGoT. The discharge of the Chaopraya River in September
was more than 600 ­m3 ­s−1, which was 3 times larger than the
discharge of the Bangpakong River (Fig. 4a). Nevertheless,the lowest salinity was from the Bangpakong River, as inAugust. Surface chlorophyll-a concentrations in the northernpart of the UGoT were higher than in the southern part. The
maximum chlorophyll-a concentration was 28.3 mg ­m−3 atstation 4. Although the chlorophyll-a concentration was relatively high (10.4 mg ­m−3) at the mouth of the BangpakongRiver, where surface salinity was lowest, the surface chlorophyll-a distribution pattern did not generally correspond tothat of surface salinity. Moreover, the bottom DO (hypoxia),
surface salinity, and surface chlorophyll-a distribution patterns all differed.
In November 2014, hypoxic water masses were observedin the northwestern part of the UGoT. The DO concentrations at stations 4–6 were 0 mg ­l−1. Meanwhile, thehypoxia off the Bangpakong River observed in September
disappeared. The distribution pattern of surface salinity inNovember differed markedly from that in September, withthe lowest salinity water mass being located in the northwestern part of the UGoT and salinity contour lines trending north–south. This finding suggests that water masses
originating outside the UGoT intruded into the UGoT fromthe eastern part of the bay mouth, and water with lower
salinity was transported to the west. Surface chlorophylla was low (< 2 mg ­m−3) in the eastern part of the UGoT,
where surface salinity was high, and chlorophyll-a was high(> 3.5 mg ­m−3) in the western part, where surface salinity
was low. The distribution of hypoxic water masses appears
to correspond to the area of low surface salinity and highsurface chlorophyll-a.
No hypoxic water masses were observed in December
2014, February 2015 or April 2015, when bottom DO concentrations were above 5 mg ­l−1, and surface chlorophyll-aconcentrations were higher than in December 2014 or April
2015 near the coast. The chlorophyll-a distribution patternin December 2014 was similar to that in November. During
these months, surface salinity was relatively high, as riverdischarges were smaller (Fig. 4a). Moreover, stratification
was weak in these periods due to strong winds during the dry
season. In June 2015, a hypoxic water mass again appeared
off the Chaopraya River; the DO concentration at station 2
was 1.5 mg ­l−1. As river discharge was not large at this time,surface salinity in June was relatively high throughout the
UGoT. Surface chlorophyll-a concentrations were higher in
the northern than southern part, with a maximum concentration of 5.4 mg ­m−3 at station 3.
Zonal sections of DO and density at the northern observation stations (stations 1–5) from June to November,when hypoxia occurred (Fig. 3), are shown in Fig. 5. Weakstratification was recorded at stations 2 and 5 in June, anda water mass with low DO (< 3 mg ­l−1) occurred only
at station 2. In August, the water column was verticallyhomogenous in the western part, and weak stratification
was present at station 2, which had begun during the rainyseason (Fig. 4a). In August, a hypoxic water mass waspresent only at station 2, and the distribution pattern of
DO was similar to that in June. Stratification developedin September, especially in the eastern part of the UGoT,
and hypoxic water masses extended from the eastern to
the western part. The thickness of the hypoxic water mass
at stations 2 and 3 was about 5 m, while station 4 and 5
had about 1 m and 2 m of hypoxic water, respectively.

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A. Morimoto et al.

Fig. 3  Horizontal distributions of observed DO at 1 m above the bottom, surface salinity at 1 m below the sea surface, and chlorophyll-aconcentration at 1 m below the sea surface from August 2014 to June

13

2015. Black lines in the figures show isolines; every 1 mg ­l−1 for bottom DO and 1 psu for surface salinity

Hypoxia in the Upper Gulf of Thailand: Hydrographic observations and modeling﻿	

(a)

(b)

Fig. 4  a Monthly mean of river discharges of five rivers shown in
Fig. 1 and total discharge (red line) from January 2014 to June 2015.
b Monthly mean of total discharge of five rivers from January 2011 toJune 2012 (colour figure online)

At station 1, the lowest DO was recorded at a depth of
9 m, indicating that a low-DO water mass had intruded
from another area. In November, stratification developed
at stations 4 and 5, and hypoxic and anoxic water masses
were observed. Surface DO was high (oversaturated) in
the western part due to a high chlorophyll-a concentration,
and DO was low at depths just below the high-DO watermass. This finding suggests that oxygen in the lower layer
is consumed locally due to the decomposition of organic
matter produced by phytoplankton.

3.2 Relationships among hypoxia, intensityof stratification and vertical supply of organic
matterIn general, hypoxia occurs due to the inhibition of vertical oxygen supply under conditions of strong stratificationand high supply of organic matter to the bottom layer,
which occur with phytoplankton blooms in surface layer.
We examined the relationships among the bottom DO
concentration, intensity of stratification and chlorophylla concentration. As an index of stratification, we used thepotential energy anomaly (PEA), calculated as follows:

PEA =

0 {
}
1
g 𝜌A − 𝜌(z) zdz,h ∫ −h(1)where h is water depth, g is gravity acceleration, 𝜌A is vertically averaged density, and 𝜌(z) is density at depth z. As
an index of organic matter, we used the vertically averaged
chlorophyll-a concentration (VAC). In September, PEA
and bottom DO had a negative correlation coefficient of− 0.42, but station 14 had low DO with weak stratification(low PEA) (Fig. 6a); the difference between surface and bottom salinities was 1.05 psu. The correlation between VAC
and bottom DO in September was weak (r = − 0.24), but
a positive correlation was found under hypoxic conditions(DO < 2 mg ­l−1) (Fig. 6b). As the VAC at station 14 wasrelatively high while PEA was low (Fig. 6a), vertical supplyof organic matter might be the main driver of hypoxia atthat location. In November, bottom DO had strong negative
correlations with PEA and VAC (Fig. 6c, d), with correlation coefficients between bottom DO and PEA, and between
bottom DO and VAC, of − 0.78 and − 0.76, respectively. Stations 5 and 6 had low DO (< 0.5 mg ­l−1), and both PEA andVAC were high. At these stations, both low vertical supplyof oxygen and high vertical supply of organic matter might
reduce DO at the bottom. As PEA at station 4 was relatively
low, whereas VAC was at its maximum, anoxic conditions
might be generated due to high organic matter supply. At
station 3, PEA was quite small (the difference between surface and bottom salinity was 0.63 psu) and VAC was notelevated; however, a hypoxic water mass was present. This
indicates that the hypoxic water mass was transported fromanother area.
Based on these hydrographic observations, we foundthat hypoxia occurred from June to November in the UGoT,
and that almost half of the UGoT by area was occupied byhypoxic water masses in September. Hypoxia appeared in
the eastern part of the UGoT in June and August, and the
hypoxic area moved westward in September and November.
In general, bottom DO had negative correlations with boththe intensity of stratification and VAC, and hypoxia wasobserved at a few stations with weak stratification and low
chlorophyll-a. This tendency might be driven by hypoxic
water masses generated in other areas that are transported
by currents. To clarify the generation process and behavior of hypoxic water masses, we investigated them using a
numerical model.

3.3 Numerical modeling results
3.3.1 Validation of the numerical model
Figure 7 shows the calculated and observed temporal variations in DO at 1 m above the bottom, and the salinity at
1 m below the sea surface, at stations 2, 4, and 6. At station

13

A. Morimoto et al.
Fig. 5  Cross section along
northern coast (Station 1–5
shown in Fig. 1) of observed
DO and density from June toNovember2, which is located off Chaopraya River mouth, the calculated bottom DO from August to mid-September was lessthan 2 mg ­l−1 and increased gradually from mid-September
to December aside from two sudden drops (early Octoberand mid-November). The high concentration of bottom
DO continued to the end of March, after which it gradually
decreased (in early May), and then increased (in May), withhypoxia occurring in June (Fig. 7a). The calculated temporalvariations of bottom DO coincide with the observed variations, although large differences were present in September
and November. The calculated surface salinity in August
was lower than the corresponding observations, and that in
September was slightly higher than the observations. The
calculated surface salinity in November, December, February reproduced the observations, but the calculated surface
salinities from March to June 2015 were much lower than13

the observed values (Fig. 7b). At station 4, located off theThachin River mouth, the calculated bottom DO was highin August and September and suddenly decreased in October, with anoxic conditions appearing in November. After
December, the high concentration of bottom DO continued
until June 2015. Although the calculated and observed bottom DO differed in September, our model reproduced theobserved temporal variations in bottom DO well (Fig. 7c).
The calculated surface salinity at station 4 accurately reproduced the observations from September to February, but was
lower than the observations in August, April, and June, as
noted at station 2 (Fig. 7d). At station 6, the calculated bottom DO was high in August and September, and dropped
suddenly at the end of September, with hypoxic conditions
lasting until the end of November. In December, bottom
DO increased, and high concentrations continued until JuneHypoxia in the Upper Gulf of Thailand: Hydrographic observations and modeling﻿	Fig. 6  Scatter plots of intensityof stratification (PEA) versus
DO concentration at 1 m above
the bottom a in September 2014
and c in November 2014. Scatter plots of vertical averaged
chlorophyll-a concentration
versus DO concentration at 1 m
above the bottom b in September 2014 and d in November
2014. Red dots denote DOconcentration less than 2 mg ­l−1
stations, and numbers denotestation number shown in Fig. 1.
Solid line in each figure shows
regression line (colour figure
online)

(a)

(b)

(c)

(d)

(Fig. 7e). The temporal variations in surface salinity were
better reproduced compared to the other two stations.
Figures 8 and 9 show the calculated monthly means ofsurface salinity, surface chlorophyll-a, and bottom DO from
August to November. Although surface salinity in the middle
and northern parts in August was lower than the observations (Fig. 3), the surface salinity distribution in September
and November coincided with the observations (Fig. 8).
Surface chlorophyll-a in August was higher than the observations throughout the study area, whereas chlorophyll-ain September was reproduced well. In November, the highconcentration along the western coast was reproduced accurately by the model, but the calculated surface chlorophylla concentrations in the eastern part were higher than theobservations, especially near the northern coast (Fig. 9).
Hypoxia around station 2 in August was reproduced. In
September, the low-DO area was smaller than the observedarea, especially near the northern coast. In November, thelow-DO area in the northwestern part of the UGoT was

reproduced. The numerical model showed seasonal movement of the hypoxic area from the eastern to the western partof the study area.
3.3.2 Horizontal distributions of salinity, surface currents,
and bottom currents
We analyzed the physical fields from August to November
2014, when hypoxic water masses were observed. Figure 8
shows the monthly means of surface salinity, surface currents, and bottom currents from August to November 2014.
The surface salinity and current fields in August and September are quite similar. At the sea surface, eastward flow at
speeds of 1–10 cm ­s−1 occurs along the northern coast, whilesoutheastward flow of about 5 cm ­s−1 occurs in the southernpart of the UGoT. On the other hand, bottom-layer currents
flow north or northeastward at about 3 cm ­s−1 to compensate
for the surface current flow. The calculated surface salinity
in August was much lower than observations, while that in

13

A. Morimoto et al.

(a)

(b)

(c)

(d)

(e)

(f)

Fig. 7  Temporal variations in DO concentration at 1 m above the bottom a in station 2, c in station 4, and e in station 6 and those in salinity at 1 m below the sea surface b in station 2, d in station 4, and e

in station 6. Solid line in each figure is calculated value of numerical model and red dot in each figure is observed value (colour figure
online)September aligned well with the observations. We found that
freshwater supplied from rivers is transported to the east by
eastward surface flow. As a result, low-salinity water accumulates in the northeastern corner of the bay. In October, thedistribution patterns of surface salinity and surface current
direction differ dramatically from those in August and September due to the arrival of strong northeast winds. A surface current (speed of about 10 cm ­s−1) flows southwestward
in the central part of the bay, while westward flow dominatesalong the northern coast, and strong southward flows with aspeed of about 20 cm ­s−1 occur along the western coast. In
the southeastern part of the bay, weak inflows are observedat the sea surface. In the bottom layer, inflow is dominant
throughout the bay. Surface currents transport low-salinity
water from river mouths to the west and south along thecoast. As a result, salinity contours shift from northwestsoutheast in September to northeast-southwest in October.
The surface and bottom currents in November are similar to
those in October, being dominated by strong currents along
the coast. As river discharges decrease at this time (Fig. 4),

the low-salinity area shrinks relative to October, while thehigh-salinity area becomes larger.

13

3.3.3 Temporal and spatial variations in surface
chlorophyll‑a and bottom DO
Figure 9 shows the surface chlorophyll-a and bottom DO
from August to November 2014.
In August, high chlorophyll-a appeared at the mouths of
the Chaopraya, Bangpakong, and Maeklong rivers. Chlorophyll-a was low along the western coast and southernpart of the UGoT, where surface salinity tended to be high.
Hypoxic water masses with DO below 2 mg ­l−1 occurred at
the mouths of the Bangpakong and Chaopraya rivers, andalong the eastern coast, and the lowest DO (< 1 mg ­l−1) was
observed off the Chaopraya River. In September, surface
chlorophyll-a was relatively high (> 10 mg ­m−3) along thenorthern coast, and the area of lower chlorophyll-a expandedin the eastern part relative to August. The bottom DO distribution in September exhibited the same pattern as that

Hypoxia in the Upper Gulf of Thailand: Hydrographic observations and modeling﻿	Fig. 8  Calculated monthly mean of surface salinity and currents at 1 m below the sea surface, and bottom currents at 1 m above the bottom from
August to November

in August, but the area of hypoxia expanded to the west. In
October, the chlorophyll-a distribution was similar to thatin September. Hypoxic water masses occupied a large areaof the UGoT, and low DO (< 1 mg ­l−1) was observed aroundthe mouths of the Bangpakong and Thachin rivers, off Chaopraya and along the western coast. The hypoxic area moved
westward from September to October. In November, surface
chlorophyll-a was high not only along the northern coast, butalso along the western coast. In contrast, low chlorophyll-a(< 1 mg ­m−3) occupied half of the UGoT, where surface
salinity was high. A water mass with high salinity and low
chlorophyll-a intruded into the UGoT from outside the bayon the northward current in the eastern part of the UGoT.
The distribution pattern of bottom DO was similar to thatin October, but the hypoxic area was smaller. The high-DO
water mass expanded to the north in the northeastern part,13

A. Morimoto et al.
Fig. 9  Calculated monthly meanof surface chlorophyll-a concentration at 1 m below the sea
surface and bottom DO concentration at 1 m above the bottom
from August to November

and the low-DO water mass expanded to the south along thewestern coast compared to October.
The hypoxic area moved from the eastern part of the
UGoT to the western part from August to November, in
accordance with the observations, and the hypoxic area waslargest in October.
3.3.4 Seasonal variations in the volume of the hypoxic
water mass
Figure 10 shows the area-averaged intensity of stratification,
calculated using Eq. (1), and the volume of the hypoxic watermass, determined based on the grids where DO was less than
2 mg ­l−1 (integrated across the whole model domain from

13

August 2014 to June 2015). The volume of hypoxia (VHyp)was relatively low in early August, increased by 30 × ­106 ­m3
in mid-August, and remained at that level until the end of
September. In October, VHyp increased suddenly, reaching a maximum of 110 × ­106 ­m3, and high-VHyp conditions
persisted until mid-November. VHyp decreased dramatically at the end of November and low VHyp persisted until
April. From the end of April, VHyp gradually increased andreached 30 × ­106 ­m3 in June.
Comparing VHyp with the area-averaged intensity ofstratification (PEA), short time-scale variations were synchronized, while a time lag was present for variations overa long time-scale. The short time-scale variations of PEA
corresponded to variations of the spring and neap tide. This

Hypoxia in the Upper Gulf of Thailand: Hydrographic observations and modeling﻿	

(a)

(b)

Fig. 10  Temporal variations in a intensity of stratification (PEA) andb volume of hypoxia from August 2014 to June 2015shows that vertical mixing due to tidal currents contributes to the development of hypoxia. Although stratification
developed in August and reached its maximum in early September, VHyp was not large in August or September. PEA
decreased in late October, but the volume of hypoxic waterremained large. In addition, PEA increased from March,while VHyp remained small in March and April.
3.3.5 Causes of hypoxia in three areas
We selected three small areas where hypoxia occurred toinvestigate how hypoxic water masses are generated (Fig. 1).
We focused on the temporal variations of DO concentrationin the bottom layer (10th layer of our model). The DO concentration varies due to both physical and biogeochemical
processes, as follows.

bottom layer, vertically integrated chlorophyll-a (VIC), andPEA within each small area.
In Area 1, the DO concentration was less than 2 mg ­l−1
from August to mid-September except for a few days; after
that, the hypoxic conditions were resolved, except in early
October (Fig. 11a). Under the hypoxic conditions in Augustand September, strong stratification developed (PEA washigh, as shown in Fig. 11f) and the PON concentration
was elevated (Fig. 11d). The values for the biogeochemicalterm were all negative, and when the PON concentration
was high in mid-August and early to mid-September, theconsumption of DO (biogeochemical term) reached about− 1.5 mg ­l−1 ­day−1. VIC varied periodically in August and
September, and the biogeochemical term varied with thesame periodicity as VIC (Fig. 11c, e). This pattern arises
because photosynthesis and respiration induced by phytoplankton vary in the bottom layer, following the variations in
VIC. In Area 1, hypoxia occurred in August and September,due to high oxygen consumption driven by an increase of the
PON concentration in the bottom layer.
In Area 2, the DO concentration decreased to about
2 mg ­l−1 from August to early September, increased in
September and decreased again from the end of September to early October. Relatively low DO conditions (about
2 mg ­l−1) continued through mid-November (Fig. 12a). The
physical term had mostly positive values and the biogeochemical term was negative (Fig. 12b, c). The PON concentration was 2–3 μM from August to mid-October, and thengradually increased by 6 μM in early November (Fig. 12d).
These variations are reflected in the biogeochemical term:
the DO consumption rate due to biogeochemical processes
increased from mid-October to early November (Fig. 12c).
The biogeochemical term did not show an increasing or
decreasing trend from August to mid-October, but shortterm variations were observed. On the other hand, the DOconcentration varied over a relatively long time scale, witha decreasing trend in August, increasing trend in September,and decreasing trend thereafter. Similar trends occurred forthe physical term (Fig. 12b). On the other hand, no such
trends were present in PEA from August to mid-October(Fig. 12f). Thus, the vertical supply of DO did not change
greatly from August to mid-October. This suggests that the𝜕DO= Physical process (advection and diffusion)
𝜕t+ Biogeochemical process (photosynthesis, respiration, decomposition)
Hereafter, we examine temporal variations in the valuesof physical and biogeochemical processes calculated by themodel. In addition, to determine the causes of variations inbiogeochemical and physical processes, we examine variations in detritus (PON; particulate organic nitrogen) in the

DO concentration in the bottom layer of Area 2 was controlled mainly by horizontal physical processes (advection
and diffusion) from August to mid-October. After mid-October, the DO concentration remained low until mid-November, although stratification weakened. During this period,

13

A. Morimoto et al.

(a)

(d)

(b)

(e)

(c)

(f)

Fig. 11  Temporal variations in a DO concentration in the bottom
layer, values of b physical term of the model and c biogeochemicalterm related to variability of DO concentration in the bottom layer,
d PON concentration in the bottom layer, e vertical integrated chlo-rophyll-a concentration, and f intensity of stratification (PEA) from
August to November 2014 in Area-1 shown as red square in Fig. 1(colour figure online)

low DO was maintained through high DO consumption
via biogeochemical processes, while high VIC (Fig. 12e)
resulted in high PON (Fig. 12d) in the bottom layer, increasing the DO consumption rate.
In Area 3, the DO concentration was high in August and
September and dropped suddenly in late September. Hypoxic
conditions continued until the end of November (Fig. 13a).
When the DO concentration dropped, PEA increased simultaneously (Fig. 13f). This finding indicates that the development of stratification is related to the occurrence of hypoxia.
After stratification had developed, the PON concentrationof the bottom layer, VIC, and biogeochemical term allincreased (Fig. 13c–e). In addition, the correlation between
the PON concentration and biogeochemical term was strong(r = − 0.94), and that between the VIC and PON concentration (with a 2-day lag) was also strong (r = 0.81). These findings suggest that the chlorophyll-a concentration increasedin late September due to the development of stratification; asa result, the PON concentration increased due to the supplyof organic matter and the DO consumption rate increased
with the decomposition of PON. Therefore, the hypoxia in
Area 3 was generated locally.

13

4 Influence of flooding on hypoxia
occurrence
Seasonal monsoon rains sometimes cause floods in the
Chaopraya River basin. A severe flood occurred in 2011;
it was the fifth largest flood in Chaopraya River basin since
1985, with a duration of 158 days (Gale and Saunders 2013).
Total discharge from January to May 2011 was similar tothat in 2014, but the total discharge in October 2011 (maximum discharge period) was about 3 times larger than in
October 2014 (Fig. 4). The total discharge during the dry
season (from January to June) of 2012 was about twice asHypoxia in the Upper Gulf of Thailand: Hydrographic observations and modeling﻿	

(a)

(d)

(b)

(e)

(c)

(f)

Fig. 12  Same as Fig. 11 but in Area-2 (colour figure online)

large as in 2015. The total annual freshwater supply (fromJuly to June) in 2011–2012 was 8.3 × ­1010 ­m3, which is 2.6
times greater than the level in 2014–2015 (3.2 × ­1010 ­m3).
A large amount of fresh water was supplied to the UGoT in
2011, allowing a larger hypoxic water mass to develop thanin 2014, as stratification was more developed and nutrient
inputs were larger. To investigate the effects of such large
river discharge on the volume and distribution of hypoxic
water in the UGoT, we conducted a numerical experiment. In
this experiment, river discharge data from 2011 replaced thecorresponding data from 2014, and all boundary and lateralconditions for 2014 were applied. The nutrient concentrationin each river was that for 2014–2015. Temporal variationsin the intensity of stratification (PEA) and the volume of thehypoxic water mass (VHyp) are shown in Fig. 14. The variation pattern of PEA is similar to that in 2014, but PEA from
August to November was about 1.6 times larger in 2011 thanin 2014 (Fig. 10a). In addition, PEA from March to June wasabout 2 times larger in 2012 than in 2014. This suggests thatstronger stratification developed not only during the rainyseason, but also in the dry season of 2012. The VHyp wasmuch larger in 2011–2012 than in 2014–2015; the maximum
volume in October 2011 was 270 × ­106 ­m3, about 2.5 times
larger than the volume in October 2014. The VHyp became
small in December and remained so until mid-March. After
that, the VHyp increased until June 2012. The VHyp was
130 × ­106 ­m3 in May 2012, which was larger than the maximum volume from 2014 to 2015.
Figure 15 shows the horizontal distributions of bottom
DO from August to November 2011. In August 2011, thehypoxic area (< 2 mg ­l−1) extended further west relative
to August 2014, and the low-DO area (< 1 mg ­l−1) wasmuch larger than in 2014. In September, the low-DO area
expanded to the west. In October, the hypoxic area covered
half of the UGoT, and low DO was distributed from thenortheastern to southwestern part of the UGoT. In November, the distribution of hypoxic area was similar to that in
October, but the low-DO area in the eastern part became
smaller. The distribution patterns of the hypoxic water massin the flood year of 2011 were similar to those in 2014.

13

A. Morimoto et al.

(a)

(d)

(b)

(e)

(c)

(f)

Fig. 13  Same as Fig. 11 but in Area-3 (colour figure online)

However, severe hypoxic conditions (< 1 mg ­l−1) affected agreater area in the flood year of 2011 relative to 2014.

5 Discussion and summary
We conducted hydrographic surveys in August, September,
November, and December of 2014 and February, April, andJune of 2015 to reveal seasonal variations in hypoxic conditions in the UGoT. We found that hypoxia occurs from June
to November in the UGoT, and that the hypoxic area moves
from east to west seasonally. Low-salinity water, which isdiluted river water, also shifts from east to west over time.
This pattern occurs because the rotation direction of surface
circulation reverses due to a change in the direction of monsoon winds, which are cyclonic in August and September
and anti-cyclonic in October and November (Buranapratheprat et al. 2006). As a result of the shift in low-salinity
water, the stratified area also moves from east to west. We
expected hypoxia to develop in the area of strong stratification. The DO concentration in the bottom layer and the13

intensity of stratification (PEA) generally showed a negative
correlation in September and November. However, hypoxia
occurred at a few observation stations despite weak stratification. In addition, the correlation between bottom DO
concentration and VAC showed a weak positive correlationin September and a negative correlation in November. Those
results suggest that the low-DO water mass is not generated
at the observation point, and is instead transported on currents past multiple stations.
We developed a physical-ecosystem model to reproduce
the shifts of hypoxic and low-salinity water masses andinvestigated the temporal and spatial variations of hypoxia
in the UGoT. The shift of low-salinity water and the hypoxic
area from east to west was reproduced well by the model.
According to the modeling result, the VHyp in the UGoT
reaches a maximum in October (Fig. 10b), although we did
not conduct hydrographic observations in October. This
result might be driven by river discharge, which was largest
in October (Fig. 4a), and by an area of high chlorophyll-a
covering the northern part of the UGoT (Fig. 9). This peakin river discharge leads to the strongest stratification andHypoxia in the Upper Gulf of Thailand: Hydrographic observations and modeling﻿	

(a)

(b)

Fig. 14  Temporal variations in a intensity of stratification (PEA) andb volume of hypoxia from August 2011 to June 2012 when severe
flood occurred in Chaopraya basin

supplies large amounts of nutrients. As a result, the chlorophyll-a concentration increases across a wide area, and alarge amount of organic matter sinks to the bottom, where
the DO consumption rate increases due to biogeochemical

processes (decomposition), and vertical DO supply due tophysical processes decreases due to strong stratification.
We investigated the temporal variations in bottom
DO, DO consumption rate, and PEA in three areas where
hypoxia occurs. In Areas 1 and 3, the hypoxic water massis generated locally, while in Area 2, the low-DO watermass is transported from the surrounding area. Figure 16
shows the monthly average bottom DO consumption
rate (biogeochemical term in the model) from August to
November 2014. The DO consumption rate is high in each
estuarine region and offshore of the Chaopraya and Bangpakong rivers. The region of high DO consumption shifts
westward during this season. The distribution patterns ofsurface chlorophyll-a shown in Fig. 9 are similar to thepattern of the DO consumption rate. Increasing verticalflux of organic matter results in high DO consumption in
the bottom layer.
Flooding supplies a great deal of freshwater and nutrients to the UGoT and might cause strong stratification andblooms of phytoplankton. Therefore, hypoxia is considered
likely to develop after floods. Severe flooding occurred in
2011. To explore the influence of flooding on the intensityof hypoxia, we conducted a simulation using river discharge
data from 2011 and 2012. The volume of hypoxic water was
2.5 times larger in 2011 than 2014, and the hypoxic watermass was also present in the dry season of 2011. After flooding occurred in the Chaopraya River basin, river discharge
did not decrease for a long time (Fig. 4b) due to the gentle
gradient of the Chaopraya River basin. Therefore, the influence of flooding on the marine environment continues into

Fig. 15  Horizontal distributionof monthly mean of DO concentration at 1 m above the bottom
from August to November in
2011

13

A. Morimoto et al.
Fig. 16  Horizontal distribution of monthly mean of DO
consumption rate at 1 m above
the bottom from August to
November 2014

the following year, driving hypoxia in April and May 2011,as shown in Fig. 14. As hypoxic conditions persist for a longtime during flood years, dramatic decreases in the abundanceof benthic organisms are likely.
Nutrient concentrations in rivers around the UGoT werehigh; our observational data show that the maximum DIN
concentrations of the Chaopraya and Thachin rivers are
245 and 300 μM, respectively. A red tide of Noctiluca
occurs offshore of the Chaopraya and Bangpakong rivers
annually (Lirdwitayaprasit et al. 2006). Enormous amountsof organic matter may accumulate in the bottom sediment,
releasing nutrients. Even with a reduction of nutrient
fluxes from rivers through improved sewage treatment,
hypoxia is likely to persist for a long time in the UGoT.
Nutrient management is essential to protect the marine
environment of the UGoT.
Acknowledgements We appreciate captain and crews of research
vessel of Kasetsart University and students in Department of Aquatic
Science, Faculty of Science, Burapha University for their help duringhydrographic observations. This research was financially supportedby the Japan Society for the Promotion of Science, Grant-in-Aid for
Scientific Research (B) (26302001) and is partially supported by JSPS
Core-to-core CREPSUM JPJSCCB20200009.

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