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Assessment of Spatio-Temporal Variations in Water Quality of Bandon Bay, Thailand

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Assessment of Spatio-Temporal Variations in Water Quality of Bandon Bay, Thailand Indian Journal of Geo-Marine Sciences Vol. 44(7), July 2015, pp. 1000-1010 Assessment of spatio-temporal variations in water quality of Bandon Bay, Thailand Chumkiew S., Jaroensutasinee K., & Jaroensutasinee M.* Centre of Excellence for Ecoinformatics, School of Science, Walailak University, 222 Thaiburi, Thasala, Nakhon Si Thammarat, 80161, Thailand Received 27 November 2013; revised 25 February 2014 Multivariate statistical techniques were used to analyse a ten-year water quality dataset. Monthly water samples were collected from 15 river mouths during 2002-2011 and analysed for spatio-temporal variation. The results indicated that water quality at Bandon Bay varied spatially and temporally during the past ten years. Four pollution factors were identified: (1) nutrient, (2) organic matter, (3) salinity and buffering and (4) erosion factors. Discriminant analysis on spatial variables identified only four parameters - i.e. water depth, alkalinity, salinity, and temperature - to discriminate between 15 river mouths. Salinity was the only parameter that discriminated between seasons. [Keywords: Water quality, Spatial variations, Seasonal variations, Multivariate statistical techniques, Discriminant analysis] Introduction mangrove forests, and agricultural land around the Estuary water quality has been subject to the coastal area into large-scale shrimp farms16,17. consequences of a full range of anthropogenic Agricultural plantations in the area give rise to a activities, e.g. urban, industrial, and agricultural common practice of nitrogenous fertiliser usage. activities, and natural processes, e.g. precipitation, With no wastewater and sewage treatment plant erosion and weathering1-6. Estuary waters are available, several villages and towns with a highly vulnerable to pollution due to their easy population of nearly 1,100,000 directly discharge accessibility to the disposal of wastewaters. untreated wastewater into Bandon Bay. Excessive Pollution load and its concentration are seasonal cutting of the mangrove forest, over-development and largely affected by precipitation, surface of aquaculture, discharge of wastewater runoff, interflow, and groundwater flow3,7,8,9. containing degradable organic, nutrients and Information on water quality is important for the pathogen organisms from domestic effluents, and implementation of sustainable water-use agricultural runoff have resulted in a decrease in management strategies10,11,12. Assessing spatio- water quality and growing sedimentation temporal variation of water quality at river estuary problems in the bay18. is important for characterising the physical Long-term systematic and well-planned water features of aquatic environments8,13,14. Seasonal quality monitoring programs are a good approach changes in natural processes such as temperature, to improving the knowledge of estuary physiology precipitation, and hydrological condition, and hydrochemistry. However, water quality influence water quality in such a way that it monitoring is difficult due to the complexity presents different characteristics in different associated with analysing the large number of seasons7,13. available data and interpreting them19,20. Statistical Bandon Bay, a well-developed mangrove analysis can help to assess the underlying forcing forest, formerly served as a nursery ground and mechanisms. Application of different multivariate feeding area for juvenile shellfish of great statistical techniques, such as cluster analysis economic importance15,16. Regardless of its long (CA), factor analysis (FA), and discriminate association with a full range of human activities analysis (DA) has been used widely in recent and huge environmental problems, Bandon Bay years for analysing environmental data. serves as an excellent area for shellfish Multivariate statistical techniques help in the aquaculture of high commercial value. During interpretation of complex data matrices to better 1994 local people converted available wasteland, understand the water quality and ecological status CHUMKIEW et al.: ASSESSMENT OF SPATIO-TEMPORAL VARIATIONS IN WATER QUALITY 1001 of the systems under study, and the identification in November and January is the driest month of of possible factors that influence water systems. the year. The average annual temperature is 26.45 They provide a valuable tool for management of °C with the warmest month in April and the water resources, as well as rapid solution to coolest month in December. Bandon Bay is pollution problems4,7,21,22,23. This study attempts to exposed to monsoon weather with northeast winds describe the spatio-temporal variability in estuary from November to April, and southwest winds water quality, and identify the main pollution from May to October. In the lower part of the tidal factors and sources affecting water quality. ranges are muddy soils whereas acid sulphate soil is found in the upper part. The major surface Materials and Methods freshwater discharge into Bandon Bay is from the Bandon Bay is among the most productive Tapi-Phum Duang River watershed with approximately 13,737 million m3 in annual coastal areas in southern Thailand (Fig. 1). It is 25 located in Surat Thani province, southern runoff . Thailand (Latitude 9º 7′-9º 25′ N and Longitude The Tapi River and its 18 channels are the 99º 9′-99º 39′ E) covering an area of 1215 km2,17. main sources of freshwater, nutrients, organic Bandon Bay is a small open bay with a coastal matter, and sediment, and act as driving flow area of gradual slope and shallow water. A large water courses that vary over the hydrological year with high rainfall concentrations in the rainy mudflat extends along the coast to about 2 km 26 from shore contributing to the high sediment rate months and deficit during dry periods . Land use within the bay24. The inner Bandon Bay from in Bandon Bay consists of mangrove forest, tropical forest, urban area, agricultural area and Chaiya District to Donsak District covers an area 16,17 of 480 km2 with 80 km of coastline with an aquacultural area . Mangrove forests of Bandon average depth of 2.9 m. Bay play an important economic role as food and The climate is characterised by constant high energy sources. Local people depend on the temperature and rainfall. During the period 1983- mangrove areas for charcoal, timber, catching 2012, the average annual rainfall is 1,530.95 mm fishes, shrimps and crabs. Aquaculture, especially ranging from 1,025.1 to 2,414.80 mm. The shrimp farming, is a traditional practice for local average rainfall in wet and dry seasons is 1,809 people and has expanded rapidly on a commercial mm and 252 mm respectively. Rainfall is highest (a) (b) Fig. 1—(a) Bandon Bay, Thailand and (b) 15 river mouths: (1) Thakrajai, (2) Thamuang, (3) Pumreing, (4) Huawao, (5) Thapoon, (6) Thachang, (7) Liled, (8) Tapi, (9) Thathongmai, (10) Changoe, (11) Kradae, (12) Ram, (13) Thathong, (14) Nui, and (15) Donsak River mouths. 1002 INDIAN J. MAR. SCI. VOL. 44, No. 7, JULY 2015 scale to meet increased national and international variables. The best discriminate function (DF) for demands. Excessive cutting of the mangrove each situation was selected, considering the forest with massive development of shrimp goodness of the classification matrix and the aquaculture has led to decreasing water quality number of parameters needed to reach such a and increasing sedimentation18. matrix8,30. Monthly water samples were collected from 15 river mouths at Bandon Bay over a ten-year Results and Discussion period (2002-2011). The 15 river mouths were (1) Thakrajai, (2) Thamuang, (3) Pumreing, (4) Spatial and temporal variation of water quality Huawao, (5) Thapoon, (6) Thachang, (7) Liled, Wet season had lower water temperature, (8) Tapi, (9) Thathongmai, (10) Changoe, (11) transparency, salinity, pH, alkalinity, and higher Kradae, (12) Ram, (13) Thathong, (14) Nui, and BOD5, NH4-N, NO2, NO3 and PO4 than dry season (15) Donsak river mouths (Fig. 1). The (Table 1). Water depth, DO, and TSS did not physiochemical parameters, consisting of water differ between wet and dry seasons (Table 1). depth, water temperature, transparency, salinity, Box-whisker plots demonstrate the temporal and pH, dissolved oxygen, biochemical oxygen spatial variation within the 13 variables and 15 demand (BOD5), alkalinity, total suspended solids river mouths (Fig. 2a-z). Seasonal variations in (TSS), ammonium (NH4-N), nitrite (NO2), nitrate precipitation and surface runoff have a strong (NO3), and orthophosphate (PO4), were collected effect on the river discharge. The results of the over a ten-year period. These data were obtained monitoring show a seasonal fluctuation in salinity from the Surat Thani Coastal Fisheries Research indicating the influx of freshwater causing low and Development Centre (SCFRDC), Department salinity during the wet season. Extreme of Fisheries. Sampling, preservation, and fluctuations in salinity have implications for transportation of the water samples to the shrimp and shellfish aquaculture in Bandon Bay laboratory were analysed according to standard area. 27 methods . Depth, temperature, transparency, Presence of highest concentration of nutrients - salinity, pH, and DO were investigated in the i.e. NH4-N, NO2, NO3, and PO4, Fig. 2s-z - in field. Water samples were then fixed, and BOD5, November (wet season) might originate from alkalinity, TSS, NH4-N, NO2, NO3, and PO4 were overland runoff from agricultural fields where measured in the laboratory using APHA nitrogenous fertilisers are used, intensive
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