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Water quality and uses of the Bangpakong River (Eastern Thailand)
PII: S0043-1354(01)00079-3
Wat. Res. Vol. 35, No. 15, pp. 3635–3642, 2001 # 2001 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0043-1354/01/$ - see front matter
WATER QUALITY AND USES OF THE BANGPAKONG RIVER (EASTERN THAILAND) A. A. BORDALO1*, W. NILSUMRANCHIT2 and K. CHALERMWAT3 1
2
Laboratory of Hydrobiology, Institute of Biomedical Sciences, P-4099-003 Porto, Portugal; Department of Environmental Health, Faculty of Public Health, Burapha University, 20131 Chonburi, Thailand and 3 Department of Aquatic Sciences, Faculty of Science, Burapha University, 20131 Chonburi, Thailand (First received 20 March 2000; accepted in revised form 11 January 2001)
Abstract}The Bangpakong River is the most important watershed in the Eastern part of Thailand. Water quality parameters were sampled from June 1998 through May 1999 at 11 sites along a 227 km gradient, covering the wet season (June–November) and the dry season (December–May). Surface water was collected at three different stations per site (close to the banks and in the middle of the river), and analyzed for temperature, dissolved oxygen, turbidity, suspended solids, pH, ammonia, fecal coliforms, biochemical oxygen demand and chemical oxygen demand as well as conductivity, phosphate, and heavy metals. The Scottish water quality index (WQI) was adaptated to the tropical environment. The averaged WQI was low (41%) and quality declined significantly during the dry season (ANOVA, p50:001). Although the quality rose somewhat at middle sites, only 27% of the WQI values during wet season and 2.5% during dry season were higher than 50%, denoting poor environmental quality. Within each season, the main sources of variability were the differences between sites along the gradient (48% during the wet season, 63% during the dry season), whereas monthly variability represented less than 20% of the variability. The seasonal results show that the river is suitable only for tolerant fish and wildlife species and is of doubtful use for potable water supply during the dry season. As quality improves during the wet period, water can be used for the production of potable water, but only with advanced treatment, and for indirect and noncontact recreational activities. In the middle stretches of the river, higher water quality permits multiple uses at moderate cost. # 2001 Elsevier Science Ltd. All rights reserved Key words}water quality index, pollution, heavy metals, Thailand, Bangpakong River
INTRODUCTION
The Bangpakong River is the most important watershed in the eastern part of Thailand and is a crucial source of water for irrigation, as well as for heavy and light industries, aquaculture, animal farming, municipal supply and wastewater dilution. The watershed covers 18,500 km2 (Fig. 1), and the river results from the conjunction of two smaller rivers, the Hanuman and Praprong, 220 km upstream from the river mouth (138500 0200 N, 1018410 4600 E). The river drains into the Gulf of Thailand and, during the dry season, salt intrusion can travel 150 km upstream. Two provinces are within the watershed limits namely, Chachoengsao, close to the coast, and Prachinburi, inland. Different agencies regularly survey the water quality along the river and their tributaries. Although Thai standards (NEB, 1994)
*Author to whom all correspondence should be addressed. Tel.: +351-222062284; fax: +351-222062284; e-mail: [email protected]
are in line with European (for example 75/440/EEC and 76/160/EEC) and US standards (for example Clear Water Act), sampling strategies and analytical procedures are not always compatible, leading to intercomparison difficulties. Moreover, each parameter is analyzed individually by comparing to the corresponding standard value, thus making the interpretation of overall water quality difficult, because of the multiples uses desired. Water quality indices are intended to provide a simple and understandable tool for managers and decision makers on the quality and possible uses of a given water body. Basically, a water quality index (WQI) attempts to provide a mechanism for presenting a cumulatively derived, numerical expression defining a certain level of water quality (Miller et al., 1986). The first WQI was developed in the United States by Horton (1965) and applied in Europe since the 1970s, initially in the United Kingdom. It has also found applicability in Africa and Asia (Shoji et al., 1966; Handa, 1981; Suki et al., 1988; Bhargava, 1987; Al-Ami et al., 1987; Zou et al., 1988; Sahu et al., 1991; Erondu and Nduka, 1993; Palupi et al., 1995).
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The WQI approach has many variations in the literature and comparative evaluations have been undertaken (SDD, 1976; Ott, 1978; Dunnette, 1979; Miller et al., 1986). In order to assess the present water quality and the possible uses of the Bangpakong River, a WQI was applied to a data set expressly collected for this study. It is based on the Scottish WQI (SDD, 1976) and specially adapted to tropical conditions (see below), in order to generate a score describing general water quality for the monsoon-influenced river during the wet and dry seasons.
MATERIALS AND METHODS
Sampling area The Bangpakong River watershed is strongly influenced by the wet Southeast monsoon from late May to October– mid November and the dry Northeast monsoon, during the late November–February period, thus generating two wellmarked seasons. Usually, the wet season lasts from June to November and the dry season from December to May. Air temperatures ranged from 23.88C to 32.68C, with a yearly average of 27.98C. Rainfall averaged 1315 mm for the period 1961–1991, and the number of rainy days covered one third of the year. Usually September has maximum rainfall. Concomitantly, about 96% of the annual river discharge occurs during the wet season. Recalculating the data from Boonphakdee et al. (1999) for the period 1993– 1996, the total annual freshwater discharge into the inner Gulf of Thailand averaged 8.44 km3 (512 m3 s1 during the wet season and 21 m3 s1 during the dry season). The soil is mainly hard clay with a pH close to 7.5, rich in iron and phosphorous. Land use is diverse (Table 1), ranging from rubber forests and orchards in the upper reaches, to paddy fields, shrimp, fish and pig farms in the middle and lower reaches. The right bank of the lower stretch of the river is strongly influenced by dozens of irrigation canals connecting the Bangpakong River watershed with the neighboring Bangkok metropolitan area Chao Phraya watershed (Fig. 1). Sampling strategy The main course of the Bangpakong River (220 km) was divided into nine stretches to take advantage of the presence of bridges for sample collection. In addition, two other sites were established in the upstream tributaries, the Hanuman (site 10) and Praprong rivers (site 11), just before their conjunction to form the Bangpakong River. At each site,
Table 1. Land use in lower (Chachoengsao Province) and upper (Prachinburi Province) Bangpakong watershed (in percentage) (adapted from PCD, 1998)
Forest Grassland Orchards Paddy fields Plantations Uncultivated land Urban Vegetables Othera a
Chachoengsao
Prachinburi
22.4 0.1 4.5 29.8 19.0 1.4 1.2 0.4 21.2
23.8 0.1 2.2 22.7 15.7 0.7 1.0 0.3 33.4
Includes inland aquaculture (shrimp and fish farming) and pig and poultry farms.
samples from the first 30-cm of the water column were collected at three stations}close to the right and left banks and in the middle of the river}by means of an acid-washed, plastic bucket, previously rinsed with water from each station. Subsamples were stored in acid-washed plastic bottles (chemistry) and sterile glass flasks (bacteriology), cooled, transported to the laboratory and processed within 6 h of collection. The 11 sites were visited monthly from June 1998 through May 1999, covering one wet and one dry season. Analytical procedures A total of nine parameters were included in the WQI}temperature, dissolved oxygen, turbidity, pH, ammonia, suspended solids, biological oxygen demand (BOD5), chemical oxygen demand (COD), fecal coliforms. In addition, conductivity and phosphate were also measured monthly. Heavy metal analyses were also performed once per season, for Hg, Cu, Fe, Zn, and Cd. 1. Field measurements Temperature and conductivity were measured with a Jenway meter (model 4200), pH with a Testo meter (model 251), dissolved oxygen with a WTW meter (model Oxi230) and turbidity (in NTU units) with a Lovibonol meter (model DRT-15). Instruments were calibrated prior to use according to the manufacturer’s directions. 2. Chemical and bacteriological analysis Phosphate was assayed by persulfate digestion and the ascorbic acid method (APHA, 1992). Samples were stabilized by adding HgCl2. Ammonia was determined by direct nesslerization and distillation in samples pre-treated with H2SO4 (APHA, 1992). Suspended solids were assayed by filtering a suitable amount of sample through a precombusted GF/C glass fiber filter according to Standard Methods (APHA, 1992). BOD5 was determined as the difference between initial and 5-day oxygen concentrations in bottles assayed by the Winkler method, after incubation at 208C. COD was assayed by means of the closed reflux, titrimetric method (APHA, 1992). Heavy metals Hg, Cu, Fe, Zn and Cd were assayed by atomic absorption spectrometry in a GBS AA spectrometer. All samples were pre-treated with HNO3 according to Standard Methods (APHA, 1992). Fecal coliforms were assayed according to ISO 9308/1 (ISO, 1990) standard. Bacteria were concentrated onto 0.45 mm sterile membrane filter, placed into Petri dishes containing mFC culture media (Merck 10426), incubated for 24 h at 44.58C and counted. Water quality index A modified Scottish water quality index (SDD, 1976) was applied to the tropical Bangpakong River. The number of parameters was reduced from the original 10 to 8. Conductivity was excluded since, during the dry season brackish water can be found as far as 150 km from the river mouth. Nitrate analysis was not performed due to methodological difficulties associated to high turbidity and color of the river water. Raw data for each individual parameter, namely temperature, dissolved oxygen, turbidity, pH, ammonia, suspend solids, BOD, COD and fecal coliforms were compared to standard curves in order to generate a water quality rating (SDD, 1976; Tyson and House, 1989). However, temperature curves were adapted to local environmental characteristics by shifting values 118C to the right. This adjustment was based on the averaged optimal temperature (278C) for eight different fish species common in the Bangpakong River (e.g. Boonrath, 1980 for snake skinned gourami, Hora and Pillary, 1962 for Thai silver barb). The final, modified, arithmetic, weighted index is the result of squaring the sum of the products of water quality
Water quality in Bangpakong River, Thailand
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Fig. 1. Bangpakong River watershed (Eastern Thailand) and location of sampling stations.
ratings (qi ) and weighting each individual parameter (wi ) divided by 100, according to the following equation:
WQI ¼ 1=100
9 X
!2 qi wi
:
i¼1
Since the original index included 10 parameters, the weight of each individual parameter was scaled up in proportion calculations, in order to give a final parameter weight of 1.00 (SDD, 1976). Data treatment All chemical and bacteriological analyses were performed in duplicate and the results averaged. Fecal coliform data were log-transformed in order to stabilize the variance. Statistics were performed with the Statgraphics software package. When appropriate, individual station averaged values are presented with standard errors. All original, unadapted algorithms used for WQI computations were supplied by Mano (1989). The water quality map was generated with Surfer software and kriging was used as a interpolating method.
RESULTS
1. Environmental variables Surface water temperature ranged between 26.28C and 34.98C in the dry season (DS) and 26.38C and 35.68C in the wet season (WS) (Fig. 2(A)). Temperature increased steadily from upstream to the river mouth and no significant differences were found between seasons (ANOVA, p > 0:05). Cross-section
differences within each sampling stations were also not statistically significant (ANOVA, p > 0:05). Due to runoff from surrounding paddy fields and orchards, shrimp and pig farms, turbidity was always high (Fig. 2(B)). However, water transparency decreased significantly during the DS, when turbidity averaged 69.9 6.3 NTU against 30.9 2.2 NTU in the WS. A positive correlation with suspended solids (r ¼ 0:673, p50:0001) was found only during the WS, denoting a seasonal influence of allochthonous material. Waters of Bangpakong River were also characterized by low oxygen content during the DS, with percentage saturation ranging from 32.6% to 69.4% (average 48.8 0.6%) (Fig. 2(C)). Averaged monthly percentage of saturation values for each station were never higher than 60, with most stations under 50. These dissolved oxygen values were significantly lower (ANOVA, p50:001) than during the WS, when oxygen saturation averaged 71.6 1.3% and averaged monthly concentrations never dropped below 60%. Fecal coliform (FC) numbers were usually low, from 20 to 2403 cfu/100 ml (average 596 33 cfu/ 100 ml) in the DS and from 7 to 1486 cfu/100 ml (average 278 24 cfu/100 ml) in the WS (Fig. 2(D)). The survival of indicator bacteria was more related to environmental variables during the WS than during the DS (Table 2). However, higher temperatures had a deleterious influence, as shown by a significant
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Fig. 2. Spatial and seasonal dynamics of selected variables in Bangpakong River in 1998/1999. Monthly data were seasonally averaged (square}wet season; circle}dry season). The bar denotes SE. (A) temperature; (B) oxygen saturation; (C) turbidity; (D) fecal coliforms; (E) BOD5; (F) COD; (G) ammonia (NH4); (H) phosphate (PO4). Table 2. Spearman rank correlation coefficients (r) between fecal coliform bacteria (FC) and environmental variables in Bangpakong River. ns=non significant, n¼ 1352162
Temperature Oxygen saturation Turbidity Suspended solids Salinity pH BOD COD Ammonia Phosphate a b c
Dry season
Wet season
0.412a 0.433a 0.278b ns 0.279b 0.186c ns 0.273b 0.246b ns
0.266b 0.149c ns ns 0.235b ns ns 0.207c ns ns
p50:0001. p50:005. p50:05.
negative correlation with coliform bacteria numbers (Table 1). FC numbers increased significantly with the decrease of oxygen saturation in the water, regardless of season (Table 1). Phosphate values showed clear seasonal differences (Fig. 2(E)) with higher values in the WS. During the DS, variability between stations was not statistically
significant (ANOVA, p > 0:25). Values were in the range 0.11–2.30 (WS average 0.62 0.03 mg/l) and 0.04–1.51 mg/l (DS average 0.33 0.02 mg/l). Ammonia concentration evolved in a similar fashion (Fig. 2(F)), and values were in the range 0.02– 0.71 mg/l (WS average 0.26 0.01 mg/l) and 0.01– 0.53 mg/l (DS average 0.13 0.01 mg/l). BOD values, which measures the concentration of labile organic matter, showed little spatial or temporal variation (Fig. 2(G)), ranging from 0.33 to 1.72 mg/l in the WS (average 1.24 0.04 mg/l) and 0.24–3.11 in the DS (average 1.36 0.04 mg/l). On the other hand, COD, a measure of total oxidable organic matter had both spatial and temporal variation (Fig. 2(H)). Average values increased dramatically in the DS to 68.5 6.7 mg/l from 27.5 2.0 mg/l in the WS, and increased downstream, denoting the possible effect of the multiple Bangkok area left bank tributaries (Fig. 1). 2. Heavy metals The results for heavy metals obtained during October 1998 (WS) and February 1999 (DS) sam-
Water quality in Bangpakong River, Thailand
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Table 3. Heavy metal concentrations in Bangpakong River in October 1998 (wet season) and February 1999 (dry season) Dry season a
Wet season
Station
km
Hg (ppb)
Cu (ppm)
Fe (ppm)
Zn (ppm)
Hg (ppb)
Cu (ppm)
Fe (ppm)
Zn (ppm)
1 2 3 4 5 6 7 8 9 10 11
8 42 58 87 121 153 171 195 220 223 227
0.978 0.453 0.463 0.261 0.710 0.491 0.821 0.185 0.992 0.467 0.195
0.008 0.020 0.014 0.007 0.022 0.005 0.008 0.004 0.005 0.004 0.011
6.716 4.849 3.913 2.265 2.166 1.169 2.612 2.591 3.292 3.569 3.433
0.450 0.374 0.458 0.243 0.346 0.173 0.204 0.146 0.148 0.157 0.191
1.257 0.975 0.478 0.391 0.121 0.145 0.116 0.175 0.210 0.100 0.098
0.102 0.108 0.113 0.095 0.104 0.096 0.090 0.086 0.088 0.095 0.082
2.020 2.010 1.826 1.807 1.627 1.757 3.443 1.777 1.936 2.802 2.036
1.382 1.365 1.517 1.530 1.506 1.567 1.470 1.604 1.546 1.513 1.481
a
Distance upstream from river mouth.
Fig. 3. Spatial and seasonal averaged water quality indices SE for Bangpakong River in 1998/1999 (square }wet season; circle}dry season).
plings are summarized in Table 3. During DS, Zn concentrations were always higher than Thai standards (NEB, 1994) for both fresh and marine waters, and increased from upstream to the river mouth. During the WS, only brackish samples at sites 1–5 were higher than the standard. Iron concentrations in brackish–marine waters during low runoff were much higher than standard values. No standard exists for freshwater. Mercury concentrations were always lower than standard values regardless of season, while Cu concentrations were rather higher in brackish–marine samples during the DS. Cd values were always below detection limit (0.05 ppb). A clear difference between October (WS) and February (DS) samplings was evident. Hg, Fe and Zn values were significantly higher during the WS (ANOVA, p50:01, p50:01 and p50:05, respectively), probably due to higher runoff from land, whereas the concentration of copper was, on average, one order of magnitude higher DS. 3. Water quality index Overall water quality was significantly lower (Anova, p50:001) during the DS (Fig. 3). Average values of the WQI ranged 22.0–52.2% (average 37.4 0.5%) in the DS and 27.6–61.6% (average 43.5 0.7%) in the WS. Along the river, water quality rose at intermediate sites between 42 and 200 km from July through October and in a short
segment of the river between 121 and 172 km from December to April (Fig. 4). During the WS 27% of the WQI values (n ¼ 163) were higher than 50%, whereas in the DS the number decreased to only 2.5% (n ¼ 162). Along the river, the main source of variability within each season were the differences between sampling sites (48% for the WS, 63% for the DS). The amount of monthly variability during the WS represented 19%, whereas during the DS accounted for 20%. It should be noted that crosschannel differences in the WQI during the DS contributed to much less variability (17%) than during the WS, when the amount reached 33%. From stepwise regressions of all parameters on WQI values, it was found that during the WS, oxygen, suspended solids, fecal coliforms and BOD explained 53% of the WQI variability (p50:0001), whereas in the DS additional parameters such as temperature and turbidity explained already 91% of the variability (p50:0001).
DISCUSSION
The evaluation of overall water quality is not an easy task particularly when different criteria for different uses are applied. Moreover, the classification of water quality follows various definitions with respect to the contents of different water parameters (Greve, 1990), and dozens of variants have been developed (Smith, 1989). In this report the application of the water quality index approach to the Bangpakong River in Thailand had the purpose of providing a simple, valid method for expressing the results of several parameters in order to assess the water quality. Assembling different parameters into one single number, leads to an easy interpretation of index, thus providing an important tool for management purposes. Although the Scottish WQI (SDD, 1976) was implemented in this study, some modifications were made to account for the tropical environment. For example, the standard temperature curve was
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Fig. 4. Mapping of monthly averaged water quality indices along the gradient of Bangpakong River from June 1998 to May 1999 (10% lowest quality; 100% highest quality).
adapted to the river range, using natural fish populations optimal temperature (278C=99%), instead of the original, salmon-based curve (168C=99%). Conductivity was not included due to salt intrusion during the low discharge period of the year. Other authors also have excluded this parameter from the final index (Palupi et al., 1995). Nevertheless, correlation analysis between WQI and conductivity showed a highly significant (p50:0001) negative relationship (r ¼ 0:341 for the DS and r ¼ 0:375 for the WS) denoting poor water quality, even without having such parameter in consideration for the WQI calculations. For each sampling site a final WQI was produced from standard or adapted curves and associated parameter weighting. According to the SDD (1976), a modified arithmetic weighted index is acceptable for water quality assessment, because it overcomes the unrepresentativeness of the arithmetic indices at the lower end of the water quality scale. Moreover, the scale was considered in the range 10–100% instead in the original 0–100%, because water in Bangpakong River with a WQI510% is still acceptable for such a low demanding quality use as navigation. The present study shows that overall water quality of Bangpakong River was low, particularly during the DS, when WQI averaged 37.4 0.5% in a scale 10–100%. Similar low WQI’s and seasonal trends have been reported in rivers in Southeast Asia (Palupi et al., 1995). A combination of low discharge and higher residence times of water with continuous discharge of agriculture, industry and urban point and diffuse polluted waters fostered the decline of water quality. A serious problem that affects light penetration and navigation, an important water use for Bangpakong River, as well as represents an additional source of labile and refractory organic matter to the water is the massive growth of water hyacinth in some stretches of the river. This phenomenon is particularly important during the DS, when the highest values of COD were recorded coinciding with the highest load of suspended solids. On the other hand, in the lower reaches blooms of marine phytoplankton are common during the WS when the concentration
of nutrients increases (Fig. 2). These blooms induce massive kills of fish in fish farms located within the river, mainly due to the decrease of dissolved oxygen resulting from decay of algal biomass (Sawangwong and Fujiwara, 1994). In this study, the percentage of oxygen saturation was lowest during the DS when all sites showed values 560%. The situation improved dramatically when river flow increased and residence times decreased. Although discharge rates for the studied period were not available, in 1993/1996 the average flow at the river mouth, was 512 m3/s during the WS, whereas during the driest period it dropped to only 21 m3/s (Boonphakdee et al., 1999). From stepwise regression it was found that oxygen was the parameter that played the most crucial role in determining variations in WQI in the driest period of the year (R2 ¼ 0:57; p50:0001). The concentrations of fecal indicator bacteria (FC) were rather low, particularly during the WS. The combination of high temperature, that showed a statistically significant negative correlation with FC (Table 2), as well as particulate matter and rather high concentration of bactericidal heavy metals (Table 3) such as copper and zinc may have contributed to the elimination of FC from the water column. On the other hand, the spices commonly used in Thai cuisine are well known to have antibacterial properties (e.g. Sasser et al., 1974; Cha et al., 1983; Hefnawy et al., 1993). Whether they are responsible for lowering FC in raw sewage and concomitantly the bacterial load into Bangpakong River is still unknown. Nevertheless, it should be noted that FC bacteria were essential in determining variations in the WQI during the WS (stepwise regression, R2 ¼ 0:27, p50:0001). During the DS, the concentration of heavy metals increased in the lower reaches of the river (Table 3). Several factors may have contributed to this situation, namely: (i) the location of polluting industries such as metal plating, electronics, cable manufacture, batteries and chemical among others, (ii) the interconnection of the Bangpakong River with the neighboring polluted Chao Phraya River (Fig. 1) through multiple manmade and natural canals and finally (iii) the decrease of river flow, and concomi-
Water quality in Bangpakong River, Thailand
tant decrease of dilution. Besides the water column, the sediments in the estuary have been contaminated during the last 30 yr with copper, zinc and lead (Cheevaporn et al., 1994). Using the rating scale proposed by House and Ellis (1987) which takes into account EU water quality criteria, an index ranging between 40% and 50% means that the water needs advanced treatment for the production of potable water as well as for most industrial uses and can be used only for indirect and non-contact, recreational activities. However, is reasonable for fisheries. On the other hand, an index between 30% and 40% is acceptable only for tolerant fish and wildlife species and is doubtful for potable water supply. The rate scale reflects both water quality and potential water use; the latter factor is of great importance in planning future water uses and is frequently forgotten (Smith, 1989). In this study, only 27% of the WQI values during the WS and 2.5% during the DS were higher than 50%, usually in the middle stretches of the river, showing the need of urgent measures in order to increase water quality. Nevertheless, further work must be done in order to apply such index scale to Thai legislative criteria.
CONCLUSIONS/RECOMMENDATIONS
1. The application of a water quality index to the Bangpakong River allows a water quality classification both spatially and temporally that is reproducible within the watershed by means of uniform, objective criteria. 2. Such an approach permits the identification of stretches of the river that may require urgent measures in order to restore minimal water quality for uses other than navigation, and can be applied beyond the Bangpakong watershed. 3. The next steps consists of: (i) incorporating within the index Thai legal criteria for water quality (NEB, 1994) taking into account the dichotomy between freshwater and marine water and (ii) associating economic analysis to water quality evaluation in order to estimate the economic effect resulting from the improvement or continued deterioration of water quality. Acknowledgements}The authors are thankful to A. Mano for supplying the original WQI algorithms, to R. Claro for performing the algorithms adaptations, to W. Wiebe and two anonymous reviewers for valuable comments. The work has been undertaken under the framework of Portuguese– Thai cooperation with the support of Burapha University (Thailand).
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Wat. Res. Vol. 35, No. 15, pp. 3635–3642, 2001 # 2001 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0043-1354/01/$ - see front matter
WATER QUALITY AND USES OF THE BANGPAKONG RIVER (EASTERN THAILAND) A. A. BORDALO1*, W. NILSUMRANCHIT2 and K. CHALERMWAT3 1
2
Laboratory of Hydrobiology, Institute of Biomedical Sciences, P-4099-003 Porto, Portugal; Department of Environmental Health, Faculty of Public Health, Burapha University, 20131 Chonburi, Thailand and 3 Department of Aquatic Sciences, Faculty of Science, Burapha University, 20131 Chonburi, Thailand (First received 20 March 2000; accepted in revised form 11 January 2001)
Abstract}The Bangpakong River is the most important watershed in the Eastern part of Thailand. Water quality parameters were sampled from June 1998 through May 1999 at 11 sites along a 227 km gradient, covering the wet season (June–November) and the dry season (December–May). Surface water was collected at three different stations per site (close to the banks and in the middle of the river), and analyzed for temperature, dissolved oxygen, turbidity, suspended solids, pH, ammonia, fecal coliforms, biochemical oxygen demand and chemical oxygen demand as well as conductivity, phosphate, and heavy metals. The Scottish water quality index (WQI) was adaptated to the tropical environment. The averaged WQI was low (41%) and quality declined significantly during the dry season (ANOVA, p50:001). Although the quality rose somewhat at middle sites, only 27% of the WQI values during wet season and 2.5% during dry season were higher than 50%, denoting poor environmental quality. Within each season, the main sources of variability were the differences between sites along the gradient (48% during the wet season, 63% during the dry season), whereas monthly variability represented less than 20% of the variability. The seasonal results show that the river is suitable only for tolerant fish and wildlife species and is of doubtful use for potable water supply during the dry season. As quality improves during the wet period, water can be used for the production of potable water, but only with advanced treatment, and for indirect and noncontact recreational activities. In the middle stretches of the river, higher water quality permits multiple uses at moderate cost. # 2001 Elsevier Science Ltd. All rights reserved Key words}water quality index, pollution, heavy metals, Thailand, Bangpakong River
INTRODUCTION
The Bangpakong River is the most important watershed in the eastern part of Thailand and is a crucial source of water for irrigation, as well as for heavy and light industries, aquaculture, animal farming, municipal supply and wastewater dilution. The watershed covers 18,500 km2 (Fig. 1), and the river results from the conjunction of two smaller rivers, the Hanuman and Praprong, 220 km upstream from the river mouth (138500 0200 N, 1018410 4600 E). The river drains into the Gulf of Thailand and, during the dry season, salt intrusion can travel 150 km upstream. Two provinces are within the watershed limits namely, Chachoengsao, close to the coast, and Prachinburi, inland. Different agencies regularly survey the water quality along the river and their tributaries. Although Thai standards (NEB, 1994)
*Author to whom all correspondence should be addressed. Tel.: +351-222062284; fax: +351-222062284; e-mail: [email protected]
are in line with European (for example 75/440/EEC and 76/160/EEC) and US standards (for example Clear Water Act), sampling strategies and analytical procedures are not always compatible, leading to intercomparison difficulties. Moreover, each parameter is analyzed individually by comparing to the corresponding standard value, thus making the interpretation of overall water quality difficult, because of the multiples uses desired. Water quality indices are intended to provide a simple and understandable tool for managers and decision makers on the quality and possible uses of a given water body. Basically, a water quality index (WQI) attempts to provide a mechanism for presenting a cumulatively derived, numerical expression defining a certain level of water quality (Miller et al., 1986). The first WQI was developed in the United States by Horton (1965) and applied in Europe since the 1970s, initially in the United Kingdom. It has also found applicability in Africa and Asia (Shoji et al., 1966; Handa, 1981; Suki et al., 1988; Bhargava, 1987; Al-Ami et al., 1987; Zou et al., 1988; Sahu et al., 1991; Erondu and Nduka, 1993; Palupi et al., 1995).
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The WQI approach has many variations in the literature and comparative evaluations have been undertaken (SDD, 1976; Ott, 1978; Dunnette, 1979; Miller et al., 1986). In order to assess the present water quality and the possible uses of the Bangpakong River, a WQI was applied to a data set expressly collected for this study. It is based on the Scottish WQI (SDD, 1976) and specially adapted to tropical conditions (see below), in order to generate a score describing general water quality for the monsoon-influenced river during the wet and dry seasons.
MATERIALS AND METHODS
Sampling area The Bangpakong River watershed is strongly influenced by the wet Southeast monsoon from late May to October– mid November and the dry Northeast monsoon, during the late November–February period, thus generating two wellmarked seasons. Usually, the wet season lasts from June to November and the dry season from December to May. Air temperatures ranged from 23.88C to 32.68C, with a yearly average of 27.98C. Rainfall averaged 1315 mm for the period 1961–1991, and the number of rainy days covered one third of the year. Usually September has maximum rainfall. Concomitantly, about 96% of the annual river discharge occurs during the wet season. Recalculating the data from Boonphakdee et al. (1999) for the period 1993– 1996, the total annual freshwater discharge into the inner Gulf of Thailand averaged 8.44 km3 (512 m3 s1 during the wet season and 21 m3 s1 during the dry season). The soil is mainly hard clay with a pH close to 7.5, rich in iron and phosphorous. Land use is diverse (Table 1), ranging from rubber forests and orchards in the upper reaches, to paddy fields, shrimp, fish and pig farms in the middle and lower reaches. The right bank of the lower stretch of the river is strongly influenced by dozens of irrigation canals connecting the Bangpakong River watershed with the neighboring Bangkok metropolitan area Chao Phraya watershed (Fig. 1). Sampling strategy The main course of the Bangpakong River (220 km) was divided into nine stretches to take advantage of the presence of bridges for sample collection. In addition, two other sites were established in the upstream tributaries, the Hanuman (site 10) and Praprong rivers (site 11), just before their conjunction to form the Bangpakong River. At each site,
Table 1. Land use in lower (Chachoengsao Province) and upper (Prachinburi Province) Bangpakong watershed (in percentage) (adapted from PCD, 1998)
Forest Grassland Orchards Paddy fields Plantations Uncultivated land Urban Vegetables Othera a
Chachoengsao
Prachinburi
22.4 0.1 4.5 29.8 19.0 1.4 1.2 0.4 21.2
23.8 0.1 2.2 22.7 15.7 0.7 1.0 0.3 33.4
Includes inland aquaculture (shrimp and fish farming) and pig and poultry farms.
samples from the first 30-cm of the water column were collected at three stations}close to the right and left banks and in the middle of the river}by means of an acid-washed, plastic bucket, previously rinsed with water from each station. Subsamples were stored in acid-washed plastic bottles (chemistry) and sterile glass flasks (bacteriology), cooled, transported to the laboratory and processed within 6 h of collection. The 11 sites were visited monthly from June 1998 through May 1999, covering one wet and one dry season. Analytical procedures A total of nine parameters were included in the WQI}temperature, dissolved oxygen, turbidity, pH, ammonia, suspended solids, biological oxygen demand (BOD5), chemical oxygen demand (COD), fecal coliforms. In addition, conductivity and phosphate were also measured monthly. Heavy metal analyses were also performed once per season, for Hg, Cu, Fe, Zn, and Cd. 1. Field measurements Temperature and conductivity were measured with a Jenway meter (model 4200), pH with a Testo meter (model 251), dissolved oxygen with a WTW meter (model Oxi230) and turbidity (in NTU units) with a Lovibonol meter (model DRT-15). Instruments were calibrated prior to use according to the manufacturer’s directions. 2. Chemical and bacteriological analysis Phosphate was assayed by persulfate digestion and the ascorbic acid method (APHA, 1992). Samples were stabilized by adding HgCl2. Ammonia was determined by direct nesslerization and distillation in samples pre-treated with H2SO4 (APHA, 1992). Suspended solids were assayed by filtering a suitable amount of sample through a precombusted GF/C glass fiber filter according to Standard Methods (APHA, 1992). BOD5 was determined as the difference between initial and 5-day oxygen concentrations in bottles assayed by the Winkler method, after incubation at 208C. COD was assayed by means of the closed reflux, titrimetric method (APHA, 1992). Heavy metals Hg, Cu, Fe, Zn and Cd were assayed by atomic absorption spectrometry in a GBS AA spectrometer. All samples were pre-treated with HNO3 according to Standard Methods (APHA, 1992). Fecal coliforms were assayed according to ISO 9308/1 (ISO, 1990) standard. Bacteria were concentrated onto 0.45 mm sterile membrane filter, placed into Petri dishes containing mFC culture media (Merck 10426), incubated for 24 h at 44.58C and counted. Water quality index A modified Scottish water quality index (SDD, 1976) was applied to the tropical Bangpakong River. The number of parameters was reduced from the original 10 to 8. Conductivity was excluded since, during the dry season brackish water can be found as far as 150 km from the river mouth. Nitrate analysis was not performed due to methodological difficulties associated to high turbidity and color of the river water. Raw data for each individual parameter, namely temperature, dissolved oxygen, turbidity, pH, ammonia, suspend solids, BOD, COD and fecal coliforms were compared to standard curves in order to generate a water quality rating (SDD, 1976; Tyson and House, 1989). However, temperature curves were adapted to local environmental characteristics by shifting values 118C to the right. This adjustment was based on the averaged optimal temperature (278C) for eight different fish species common in the Bangpakong River (e.g. Boonrath, 1980 for snake skinned gourami, Hora and Pillary, 1962 for Thai silver barb). The final, modified, arithmetic, weighted index is the result of squaring the sum of the products of water quality
Water quality in Bangpakong River, Thailand
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Fig. 1. Bangpakong River watershed (Eastern Thailand) and location of sampling stations.
ratings (qi ) and weighting each individual parameter (wi ) divided by 100, according to the following equation:
WQI ¼ 1=100
9 X
!2 qi wi
:
i¼1
Since the original index included 10 parameters, the weight of each individual parameter was scaled up in proportion calculations, in order to give a final parameter weight of 1.00 (SDD, 1976). Data treatment All chemical and bacteriological analyses were performed in duplicate and the results averaged. Fecal coliform data were log-transformed in order to stabilize the variance. Statistics were performed with the Statgraphics software package. When appropriate, individual station averaged values are presented with standard errors. All original, unadapted algorithms used for WQI computations were supplied by Mano (1989). The water quality map was generated with Surfer software and kriging was used as a interpolating method.
RESULTS
1. Environmental variables Surface water temperature ranged between 26.28C and 34.98C in the dry season (DS) and 26.38C and 35.68C in the wet season (WS) (Fig. 2(A)). Temperature increased steadily from upstream to the river mouth and no significant differences were found between seasons (ANOVA, p > 0:05). Cross-section
differences within each sampling stations were also not statistically significant (ANOVA, p > 0:05). Due to runoff from surrounding paddy fields and orchards, shrimp and pig farms, turbidity was always high (Fig. 2(B)). However, water transparency decreased significantly during the DS, when turbidity averaged 69.9 6.3 NTU against 30.9 2.2 NTU in the WS. A positive correlation with suspended solids (r ¼ 0:673, p50:0001) was found only during the WS, denoting a seasonal influence of allochthonous material. Waters of Bangpakong River were also characterized by low oxygen content during the DS, with percentage saturation ranging from 32.6% to 69.4% (average 48.8 0.6%) (Fig. 2(C)). Averaged monthly percentage of saturation values for each station were never higher than 60, with most stations under 50. These dissolved oxygen values were significantly lower (ANOVA, p50:001) than during the WS, when oxygen saturation averaged 71.6 1.3% and averaged monthly concentrations never dropped below 60%. Fecal coliform (FC) numbers were usually low, from 20 to 2403 cfu/100 ml (average 596 33 cfu/ 100 ml) in the DS and from 7 to 1486 cfu/100 ml (average 278 24 cfu/100 ml) in the WS (Fig. 2(D)). The survival of indicator bacteria was more related to environmental variables during the WS than during the DS (Table 2). However, higher temperatures had a deleterious influence, as shown by a significant
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Fig. 2. Spatial and seasonal dynamics of selected variables in Bangpakong River in 1998/1999. Monthly data were seasonally averaged (square}wet season; circle}dry season). The bar denotes SE. (A) temperature; (B) oxygen saturation; (C) turbidity; (D) fecal coliforms; (E) BOD5; (F) COD; (G) ammonia (NH4); (H) phosphate (PO4). Table 2. Spearman rank correlation coefficients (r) between fecal coliform bacteria (FC) and environmental variables in Bangpakong River. ns=non significant, n¼ 1352162
Temperature Oxygen saturation Turbidity Suspended solids Salinity pH BOD COD Ammonia Phosphate a b c
Dry season
Wet season
0.412a 0.433a 0.278b ns 0.279b 0.186c ns 0.273b 0.246b ns
0.266b 0.149c ns ns 0.235b ns ns 0.207c ns ns
p50:0001. p50:005. p50:05.
negative correlation with coliform bacteria numbers (Table 1). FC numbers increased significantly with the decrease of oxygen saturation in the water, regardless of season (Table 1). Phosphate values showed clear seasonal differences (Fig. 2(E)) with higher values in the WS. During the DS, variability between stations was not statistically
significant (ANOVA, p > 0:25). Values were in the range 0.11–2.30 (WS average 0.62 0.03 mg/l) and 0.04–1.51 mg/l (DS average 0.33 0.02 mg/l). Ammonia concentration evolved in a similar fashion (Fig. 2(F)), and values were in the range 0.02– 0.71 mg/l (WS average 0.26 0.01 mg/l) and 0.01– 0.53 mg/l (DS average 0.13 0.01 mg/l). BOD values, which measures the concentration of labile organic matter, showed little spatial or temporal variation (Fig. 2(G)), ranging from 0.33 to 1.72 mg/l in the WS (average 1.24 0.04 mg/l) and 0.24–3.11 in the DS (average 1.36 0.04 mg/l). On the other hand, COD, a measure of total oxidable organic matter had both spatial and temporal variation (Fig. 2(H)). Average values increased dramatically in the DS to 68.5 6.7 mg/l from 27.5 2.0 mg/l in the WS, and increased downstream, denoting the possible effect of the multiple Bangkok area left bank tributaries (Fig. 1). 2. Heavy metals The results for heavy metals obtained during October 1998 (WS) and February 1999 (DS) sam-
Water quality in Bangpakong River, Thailand
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Table 3. Heavy metal concentrations in Bangpakong River in October 1998 (wet season) and February 1999 (dry season) Dry season a
Wet season
Station
km
Hg (ppb)
Cu (ppm)
Fe (ppm)
Zn (ppm)
Hg (ppb)
Cu (ppm)
Fe (ppm)
Zn (ppm)
1 2 3 4 5 6 7 8 9 10 11
8 42 58 87 121 153 171 195 220 223 227
0.978 0.453 0.463 0.261 0.710 0.491 0.821 0.185 0.992 0.467 0.195
0.008 0.020 0.014 0.007 0.022 0.005 0.008 0.004 0.005 0.004 0.011
6.716 4.849 3.913 2.265 2.166 1.169 2.612 2.591 3.292 3.569 3.433
0.450 0.374 0.458 0.243 0.346 0.173 0.204 0.146 0.148 0.157 0.191
1.257 0.975 0.478 0.391 0.121 0.145 0.116 0.175 0.210 0.100 0.098
0.102 0.108 0.113 0.095 0.104 0.096 0.090 0.086 0.088 0.095 0.082
2.020 2.010 1.826 1.807 1.627 1.757 3.443 1.777 1.936 2.802 2.036
1.382 1.365 1.517 1.530 1.506 1.567 1.470 1.604 1.546 1.513 1.481
a
Distance upstream from river mouth.
Fig. 3. Spatial and seasonal averaged water quality indices SE for Bangpakong River in 1998/1999 (square }wet season; circle}dry season).
plings are summarized in Table 3. During DS, Zn concentrations were always higher than Thai standards (NEB, 1994) for both fresh and marine waters, and increased from upstream to the river mouth. During the WS, only brackish samples at sites 1–5 were higher than the standard. Iron concentrations in brackish–marine waters during low runoff were much higher than standard values. No standard exists for freshwater. Mercury concentrations were always lower than standard values regardless of season, while Cu concentrations were rather higher in brackish–marine samples during the DS. Cd values were always below detection limit (0.05 ppb). A clear difference between October (WS) and February (DS) samplings was evident. Hg, Fe and Zn values were significantly higher during the WS (ANOVA, p50:01, p50:01 and p50:05, respectively), probably due to higher runoff from land, whereas the concentration of copper was, on average, one order of magnitude higher DS. 3. Water quality index Overall water quality was significantly lower (Anova, p50:001) during the DS (Fig. 3). Average values of the WQI ranged 22.0–52.2% (average 37.4 0.5%) in the DS and 27.6–61.6% (average 43.5 0.7%) in the WS. Along the river, water quality rose at intermediate sites between 42 and 200 km from July through October and in a short
segment of the river between 121 and 172 km from December to April (Fig. 4). During the WS 27% of the WQI values (n ¼ 163) were higher than 50%, whereas in the DS the number decreased to only 2.5% (n ¼ 162). Along the river, the main source of variability within each season were the differences between sampling sites (48% for the WS, 63% for the DS). The amount of monthly variability during the WS represented 19%, whereas during the DS accounted for 20%. It should be noted that crosschannel differences in the WQI during the DS contributed to much less variability (17%) than during the WS, when the amount reached 33%. From stepwise regressions of all parameters on WQI values, it was found that during the WS, oxygen, suspended solids, fecal coliforms and BOD explained 53% of the WQI variability (p50:0001), whereas in the DS additional parameters such as temperature and turbidity explained already 91% of the variability (p50:0001).
DISCUSSION
The evaluation of overall water quality is not an easy task particularly when different criteria for different uses are applied. Moreover, the classification of water quality follows various definitions with respect to the contents of different water parameters (Greve, 1990), and dozens of variants have been developed (Smith, 1989). In this report the application of the water quality index approach to the Bangpakong River in Thailand had the purpose of providing a simple, valid method for expressing the results of several parameters in order to assess the water quality. Assembling different parameters into one single number, leads to an easy interpretation of index, thus providing an important tool for management purposes. Although the Scottish WQI (SDD, 1976) was implemented in this study, some modifications were made to account for the tropical environment. For example, the standard temperature curve was
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Fig. 4. Mapping of monthly averaged water quality indices along the gradient of Bangpakong River from June 1998 to May 1999 (10% lowest quality; 100% highest quality).
adapted to the river range, using natural fish populations optimal temperature (278C=99%), instead of the original, salmon-based curve (168C=99%). Conductivity was not included due to salt intrusion during the low discharge period of the year. Other authors also have excluded this parameter from the final index (Palupi et al., 1995). Nevertheless, correlation analysis between WQI and conductivity showed a highly significant (p50:0001) negative relationship (r ¼ 0:341 for the DS and r ¼ 0:375 for the WS) denoting poor water quality, even without having such parameter in consideration for the WQI calculations. For each sampling site a final WQI was produced from standard or adapted curves and associated parameter weighting. According to the SDD (1976), a modified arithmetic weighted index is acceptable for water quality assessment, because it overcomes the unrepresentativeness of the arithmetic indices at the lower end of the water quality scale. Moreover, the scale was considered in the range 10–100% instead in the original 0–100%, because water in Bangpakong River with a WQI510% is still acceptable for such a low demanding quality use as navigation. The present study shows that overall water quality of Bangpakong River was low, particularly during the DS, when WQI averaged 37.4 0.5% in a scale 10–100%. Similar low WQI’s and seasonal trends have been reported in rivers in Southeast Asia (Palupi et al., 1995). A combination of low discharge and higher residence times of water with continuous discharge of agriculture, industry and urban point and diffuse polluted waters fostered the decline of water quality. A serious problem that affects light penetration and navigation, an important water use for Bangpakong River, as well as represents an additional source of labile and refractory organic matter to the water is the massive growth of water hyacinth in some stretches of the river. This phenomenon is particularly important during the DS, when the highest values of COD were recorded coinciding with the highest load of suspended solids. On the other hand, in the lower reaches blooms of marine phytoplankton are common during the WS when the concentration
of nutrients increases (Fig. 2). These blooms induce massive kills of fish in fish farms located within the river, mainly due to the decrease of dissolved oxygen resulting from decay of algal biomass (Sawangwong and Fujiwara, 1994). In this study, the percentage of oxygen saturation was lowest during the DS when all sites showed values 560%. The situation improved dramatically when river flow increased and residence times decreased. Although discharge rates for the studied period were not available, in 1993/1996 the average flow at the river mouth, was 512 m3/s during the WS, whereas during the driest period it dropped to only 21 m3/s (Boonphakdee et al., 1999). From stepwise regression it was found that oxygen was the parameter that played the most crucial role in determining variations in WQI in the driest period of the year (R2 ¼ 0:57; p50:0001). The concentrations of fecal indicator bacteria (FC) were rather low, particularly during the WS. The combination of high temperature, that showed a statistically significant negative correlation with FC (Table 2), as well as particulate matter and rather high concentration of bactericidal heavy metals (Table 3) such as copper and zinc may have contributed to the elimination of FC from the water column. On the other hand, the spices commonly used in Thai cuisine are well known to have antibacterial properties (e.g. Sasser et al., 1974; Cha et al., 1983; Hefnawy et al., 1993). Whether they are responsible for lowering FC in raw sewage and concomitantly the bacterial load into Bangpakong River is still unknown. Nevertheless, it should be noted that FC bacteria were essential in determining variations in the WQI during the WS (stepwise regression, R2 ¼ 0:27, p50:0001). During the DS, the concentration of heavy metals increased in the lower reaches of the river (Table 3). Several factors may have contributed to this situation, namely: (i) the location of polluting industries such as metal plating, electronics, cable manufacture, batteries and chemical among others, (ii) the interconnection of the Bangpakong River with the neighboring polluted Chao Phraya River (Fig. 1) through multiple manmade and natural canals and finally (iii) the decrease of river flow, and concomi-
Water quality in Bangpakong River, Thailand
tant decrease of dilution. Besides the water column, the sediments in the estuary have been contaminated during the last 30 yr with copper, zinc and lead (Cheevaporn et al., 1994). Using the rating scale proposed by House and Ellis (1987) which takes into account EU water quality criteria, an index ranging between 40% and 50% means that the water needs advanced treatment for the production of potable water as well as for most industrial uses and can be used only for indirect and non-contact, recreational activities. However, is reasonable for fisheries. On the other hand, an index between 30% and 40% is acceptable only for tolerant fish and wildlife species and is doubtful for potable water supply. The rate scale reflects both water quality and potential water use; the latter factor is of great importance in planning future water uses and is frequently forgotten (Smith, 1989). In this study, only 27% of the WQI values during the WS and 2.5% during the DS were higher than 50%, usually in the middle stretches of the river, showing the need of urgent measures in order to increase water quality. Nevertheless, further work must be done in order to apply such index scale to Thai legislative criteria.
CONCLUSIONS/RECOMMENDATIONS
1. The application of a water quality index to the Bangpakong River allows a water quality classification both spatially and temporally that is reproducible within the watershed by means of uniform, objective criteria. 2. Such an approach permits the identification of stretches of the river that may require urgent measures in order to restore minimal water quality for uses other than navigation, and can be applied beyond the Bangpakong watershed. 3. The next steps consists of: (i) incorporating within the index Thai legal criteria for water quality (NEB, 1994) taking into account the dichotomy between freshwater and marine water and (ii) associating economic analysis to water quality evaluation in order to estimate the economic effect resulting from the improvement or continued deterioration of water quality. Acknowledgements}The authors are thankful to A. Mano for supplying the original WQI algorithms, to R. Claro for performing the algorithms adaptations, to W. Wiebe and two anonymous reviewers for valuable comments. The work has been undertaken under the framework of Portuguese– Thai cooperation with the support of Burapha University (Thailand).
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