IJERD – International Journal of Environmental and Rural Development (2013) 4-1

Research article
erd

Predictive Model for Biochemical Component ofPhytoplankton in the River and Estuarine Systems ofthe Mae Klong River, Thailand
BOONTARIKA THONGDONPHUM*
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Pathum Thani, Thailand
Email: Boontarika_T@exchange.rmutt.ac.th

SHETTAPONG MEKSUMPUN
Faculty of Fishery, Kasetsart University, Bangkok, Thailand

CHARUMAS MEKSUMPUN
Faculty of Fishery, Kasetsart University, Bangkok, Thailand

BANTHITA SAWASDEE
Faculty of Agricultural Technology, Rajabhat Mahasarakham University, Mahasarakham,Thailand

PATTIRA KASEMSIRI
Faculty of Technology, Mahasarakham University, Mahasarakham, Thailand
Received 16 December 2012

Accepted 30 January 2013(*Corresponding Author)

Abstract As one of the four major rivers of Thailand, the Mae Klong River flows in thewest of the Kingdom and exits into the Gulf of Thailand. This research study wasconducted during February 2006 through May 2008 and found the increased levels of NH4+,NO2-+NO3-, and PO43- in the lower river and estuary areas of the Mae Klong River, which
led to the phytoplankton blooming phenomenon in such areas. Three phyta and 63 generaof phytoplanktons were discovered in the river. The dominant groups were diatoms(Plurosigma or Gyrosigma), cyanobacteria (Trichodesmium), and dinoflagellates(Peridinium and Gonyaulax). In this study, generalized linear modeling (GLM) wasapplied to examine the factors influencing phytoplankton abundance in the river systems.
The results showed that phytoplankton abundance varied according to the dissolved
inorganic nutrient (DIN), zone, and season. Thus, the predictive model should beestablished to facilitate determination of phytoplankton abundance, assessment of water
quality, and thereby more efficient management of water resources for sustainable use.
Keywords dissolved inorganic nitrogen, phytoplankton, GLM analysis, Mae Klong River

INTRODUCTION
The Mae Klong River is the most important river in the west of Thailand, with an approximate
length of 140 km and a catchment covering 22,075 km2. The river runs from Kanchanaburiprovince and flows toward the lower plain through Ratchaburi province before discharging into theGulf of Thailand in Samut Songkhram province (Thongdonphum et al., 2010). It has long been
known that changes of river flow could impact biochemical composition, including nutrient
loading, in the river and thereby phytoplankton abundance. Nutrient loading restriction is thecornerstone of aquatic eutrophication control (Smith et al., 1999) and is readily available
monitoring data of red tide/harmful algal bloom (Zhou et al., 2008). Regional Environmental
Office 8 (REO8, 2004) reported that utilization of land along the Mae Klong River for agriculture
was estimated at 83%, 58%, and 32% in Samut Songkhram, Ratchaburi, and KanchanaburiⒸ ISERD13

IJERD – International Journal of Environmental and Rural Development (2013) 4-1

provinces, respectively. According to REO8 (2007), the deterioration of water quality induced
mainly by sewage, domestic discharges, and agriculture use has contributed to phytoplankton
blooming phenomena in the estuarine and coastal zones.
OBJECTIVE
This study aims to assess the impacts of aquatic environmental factors on the variation orabundance of phytoplankton. The findings could subsequently be used to establish a biochemical
predictive model that enables better management of water resources and thereby sustainableutilization of the river and estuarine systems as well as the ecosystem.
METHODOLOGY
Sampling sites and survey plan
The surveys were conducted at 27 sampling stations (stn.) along the Mae Klong River, the stationsof which were grouped into 3 zones: the estuarine zone in Samut Songkhram province (stn.1-stn.8),
the middle zone in Ratchaburi province (stn.9-stn.18), and the upper zone in Kanchanaburiprovince (stn.19-stn.27), spanning from February 2006 to May 2008 (Fig. 1). According to therainfall patterns, Thailand is under the influence of monsoon winds (TMD, 2012). The seasons canthus be divided into rainy season (May- September), winter season (October-February), and dry
season (March-April). In addition, large amounts of water typically flow into the lower river basin
between September and February. Water samples from the 27 stations were collected during thethree seasonal periods for the 2-year interval such that all possible loading periods were taken into
consideration, hence giving rise to a total 6 sampling times: May 2006 and May 2008 (earlyloading period), November 2006 and September 2007 (mid-loading period), and February 2006 andDecember 2007 (late-loading period).
Sample collection and analysis
The general water quality factors, namely temperature, dissolved oxygen (DO), salinity and pH,
were measured with a multi-parameter probe (YSI-6600 Sonde instrument) at the sampling sites.
Samples of surface water (30 cm deep) were pre-filtered through GF/F (Whatman) and then stored
at 4oC before transporting to the laboratory for analysis of nutrients, including ammonium (NH4+),
nitrite and nitrate (NO2-+NO3-), silicate (Si(OH)4), and ortho-phosphate (PO43-), with a SKALAR
segmented flow analyzer. The samples for chlorophyll a (Chl a) and total suspended solids (TSS)
measurement were analyzed by the spectrophotometric method and the freeze-dried technique,respectively. Phytoplankton samples were collected and preserved in formaldehyde buffered
solution before being classified and enumerated with a Sedgewick-Rafter counting chamber undera light microscope.
Data analysis
Comparisons of water quality in terms of temperature, salinity, DO, pH, Chl a, and TSS among thesampling periods and zones were performed using average levels and distribution characteristics.
Least Significant Differences (LSD) or Tamhane's T2 of Post Hoc test of the one-way analysis ofvariance (ANOVA) was used for the environmental variation comparison, and the level ofconfidence greater than 95% (p < 0.05) was considered to indicate a statistically significant impact.
The Mann-Whitney test was used where a normal distribution was not observed. Based on the workof Zuur et al. (2007), GLM analysis was applied to the proposed predictive model for
phytoplankton assessment, with attention given to the goodness of fit of the model.

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14IJERD – International Journal of Environmental and Rural Development (2013) 4-1

1560000

1550000

1540000

1560000

26272524

23 22

Mae Klong
Diversion Dam

Kanchanaburi Province(Upper zone)

21

1540000

20
1918
17

1530000

1520000

1510000

1530000

1520000

16
15

Ratchaburi Province(Middle zone)

1510000

14
13
1211

1500000

1550000

1500000

1091490000

Samut Songkhram Province(Estuarine zone)

87

1480000

1490000

65
4321480000

1 Thailand
Gulf of1470000

1470000
560000570000580000590000600000610000620000Fig. 1 Sampling stations (Stn. 1–27) from the estuarine to the upper zone of the Mae Klong
RiverRESULTS AND DISCUSSION
Environmental factors
The results indicated that the Mae Klong River was influenced by freshwater runoffs, which in turncontributed to varying water quality by loading periods. Water temperatures slightly decreased withseasons (p < 0.05), and low level of salinity was detected during the early-loading period for whichlarge quantity of water flows into the river. The pH level was found to be relatively constant for theentire study area, while DO varied and markedly decreased to unsuitable levels (<4 mg/l) in theestuarine zone during the early-loading period. The levels of TSS were between 2.40 and 187.50
mg/L with higher TSS levels found in the lower and estuarine zones. The Chl a concentration
ranged between 1.34 - 14.69 Pg/l with high concentration levels mostly found in the estuarine zone.
Chl a of approximately 10 Pg/l has been regarded as the initial level for eutrophication in theestuarine zone. In addition, this study has found that the level of Chl a in the upper zone was 4.24Pg/L, which far exceeded the natural base-line level of Chl a of approximately 3.3 Pg/L
(Thongdonphum et al., 2011).
The levels of NH4+ and NO2-+NO3- varied significantly (p < 0.05) with seasons. The
concentrations of NH4+ and NO2-+NO3- varied from 0.63 to 74.47 PM and 0.40 to 24.75 PM,
respectively. Higher concentration levels were found in the lower and estuarine zones with land
utilization for agriculture, of which rice fields and aquaculture areas accounted for 108.2 and 29.1
square kilometer, respectively (NSO, 2010). The highest population density was reported at 496
people per square kilometer in Samut Songkhram province (REO8, 2008). Si(OH) 4 concentrations
ranged from 30.13 to 148.35 PM with the concentration level apparently decreasing around theestuarine stations near the river mouth. The results show that the nutrients induced by rainfalls
during the early-loading period in the three zones under the study were significantly different (p <Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2013) 4-10.05). PO43- levels ranged from undetectable to 8.07 PM with noticeably high levels in the estuarine
zone where population density and land use were high. Of concern is that PO43- concentration in theMae Klong estuary was much higher than the recommended level of 0.48 PM for the ASEAN
marine water quality (Chongprasith et al., 1999).
Table 1 The quality of water (mean±SD) along the Mae Klong River during the study period
Parameters
Temp
(oC)
Salinity(psu)DO(mg/L)
pH
Chl a(Pg/L)
TSS(mg/L)
NH4+(PM)
NO2+NO3(PM)Si(OH)4(PM)PO43(PM)

Early-loading period
UpperMiddle
Estuarine
29.3±0.730.3±0.330.5±0.5Upper
28.4±0.7

Mid-loading period
MiddleEstuarine
29.4±0.729.5±1.2

Late-loading period
Upper
MiddleEstuarine
27.1±1.1
27.8±1.3
27.6±0.9

0.1±0.0

0.1±0.0

2.5±4.7

0.1±0.0

0.1±0.0

9.1±10.5

0.1±0.0

0.1±0.0

10.5±9.6

6.0±1.6

6.2±1.4

4.8±0.87.7±1.3

6.5±1.0

5.7±1.8

6.8±2.0

7.4±1.3

6.2±1.0

7.7±0.7

8.6±0.2

8.0±0.78.5±1.0

8.7±0.2

8.2±0.6

8.5±0.6

7.8±0.5

8.1±0.4

3.7±1.5

3.8±1.1

4.5±2.0

4.8±1.9

3.1±1.2

5.4±3.0

4.1±1.5

3.4±0.9

6.8±3.917.5±7.925.6±17.932.8±23.0

21.1±15.8

20.9±10.0

30.7±19.1

11.7±5.1

16.5±6.0

27.2±43.9

3.4±2.0

9.6±4.3

12.8±5.3

2.9±2.1

7.8±3.3

19.4±9.4

2.1±1.1

11.4±9.2

22.4±17.9

4.9±2.28

8.7±4.4

13.4±4.9

6.4±2.89.0±2.0

10.8±6.3

6.0±1.4

9.2±2.8

11.0±5.2

98.9±49.2

99.6±48.7

95.8±44.873.6±5.7

73.66±5.8

69.1±8.1

64.6±7.3

66.5±4.854.5±13.6

0.2±0.1

0.7±0.4

2.2±0.8

0.2±0.1

0.8±0.4

4.4±2.4

0.2±0.1

0.5±0.3

1.8±1.1

Phytoplankton distribution
The phytoplankton community during the study period consisted of 63 genera, namely 7
Cyanophyceae, 19 Chlorophyceae, 26 Bacillariophyceae (diatoms), 10 Dinophyceae(dinoflagellates), and 1 Chrysophyceae. The amount of phytoplankton varied from 125 to 1.86x10 5unit cells/L with the highest density found around the stations in the estuarine zone. The results
showed that diatoms were the most dominant group with highest phytoplankton abundance (1.86 x
105 cells/L). Other species, such as Trichodesmium sp., Gymnodinium sp., Noctiluca sp., Ceratiumsp., Gonyaulax sp., Peridinium sp. and Protoperidinium sp., were also found in the estuarine zone
and markedly increased in the late-loading period.
Predictive model for phytoplankton
The results of GLM analysis in Table 2 show that M2 is the optimal model (Adj.R 2 = 0.400). The
model indicates that phytoplankton abundance depends on the dissolved inorganic nitrogen (DIN;NH4++NO2-+NO3-), zone, and loading period (Load). Moreover, an interaction effect exists between
Load and DIN.
Table 2 Predictive model of phytoplankton density for the Mae Klong RiverModel
M1: Total_Phyto1 = Zone1 + Zone2 + DIN
M2: Total_Phyto2 = Zone1 + Zone2 + DIN + Load +Load*DIN
M3: Total_Phyto3 = Zone1 +Zone2 +DIN + Load +Load*Zone

Adj.R2
0.254
0.400

MSE
239183423
192354102

Goodness of Fit
p = 0.913
p = 0.963

0.283

229810498

p = 0.925

A numerical example of phytoplankton abundance estimation in the estuarine zone isshown below:Ⓒ ISERD

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IJERD – International Journal of Environmental and Rural Development (2013) 4-1

Total_Phyto2 = Intercept + zone + DIN + Load + Load*DIN= 4,843.427 - 5,475.341(Zone1) - 7,211.332(Zone2) + 226.213(DIN) 16,936.047(Load1) + 194.040(Load2) + 1,060.511(Load1)(DIN) 115.320(Load2)(DIN)= 4,843.427 - 5,475.341(1) - 7,211.332(0) + 226.213DIN - 16,936.047(1)+ 194.040(0) + 1,060.511(1)(DIN) - 115.320(0)(DIN)(1)
From Eq. (1) and as shown in Table 3, the estimated values of phytoplankton or
phytoplankton density is dependent upon the levels of DIN.
Table 3 Predicted phytoplankton density in the estuarine zone during the study periods
Study period

Predicted
phytoplankton density

Early-loading period (DIN* = 23.30)
Mid-loading period (DIN* = 27.06)
Late-loading period (DIN* = 26.77)

4,739
2,663
16,977

Phytoplankton density(unit cells/l)MedianMinMax
1,600
325
63,7502,150550
7,900
3,350200
186,400* median values

CONCLUSION
This study has revealed the ability of the proposed predictive model to identify dissolved inorganic
nitrogen (DIN) as the crucial influencing factor of phytoplankton growth. DIN has greatly
influenced the phytoplankton density of the Mae Klong River and the estuary. The predictivemodel could be employed to monitor and manage eutrophication sites. In addition, the levels ofchlorophyll a well in excess of the natural base-line level (3.3 Pg/L) point to the fact that thenutrient loading is impacted by the anthropogenic and natural activities in the area. The study
results could be applied to estimate the level of phytoplankton density for more efficientmanagement of water resources and thereby sustainable utilization.
AKNOWLEDGEMENTS
The authors would like to express deep gratitude to Dr. Urairat Netharn, to Dr. Sansanee
Wangvoralak, and to all the staff members of the Marine Environmental Laboratory (Departmentof Marine Sciences) and the Sediment and Aquatic Environment Research Laboratory (Departmentof Fishery Biology), Faculty of Fisheries, Kasetsart University, for their invaluable advice andassistance.
REFERENCES
Chongprasith, P., Wiliratanadilok, W., and Utoomprurkporm, W. 1999. ASEAN marine water quality criteria
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REO8. 2004. Environmental status in the western report. Ministry of Natural Resources and Environment,Thailand.
REO8. 2007. Environmental status in the western report. Ministry of Natural Resources and Environment,Thailand.
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Smith, V.H., Tilman, G.D. and Nekola, J.C. 1999. Eutrophication: Impacts of excess nutrient inputs onfreshwater, marine, and terrestrial ecosystems. Environmental Pollution, 100, 179-196.
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