DSpace at VNU: Development of Water Quality Indexes to Identify Pollutants in Vietnam’s Surface Water

DSpace at VNU: Development of Water Quality Indexes to Identify Pollutants in Vietnam’s Surface Water tài liệu, giáo án,...

Development of Water Quality Indexes to Identify Pollutants in Vietnam’s Surface Water Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved Pham Thi Minh Hanh1; Suthipong Sthiannopkao2; Dang The Ba3; and Kyoung-Woong Kim4 Abstract: This study presents the first water quality indexes developed to evaluate surface water in Vietnam The basic water quality index (WQIB ) can be effectively used to evaluate the spatial and temporal variations of surface water quality as well as to identify water pollutants The overall water quality index (WQIO ) can provide additional information, particularly on toxic substances contributing to water pollution The water quality indexes developed for this paper were applied to the national surface-water quality monitoring data taken from 1999 to 2007 Water pollutants were classified into three subcategories: organic and nutrients, particulates, and bacteria Surface water in northern and central Vietnam was poor in quality and contained organic matter, nutrients, and bacteria Water in the southern part was mainly polluted by bacteria Trend analysis results reveal a deterioration in water quality in those provinces under pressure from rapid population growth, urbanization, and industrialization Vietnam has established an official policy to ensure comprehensive nationwide water quality monitoring by 2020 The implementation of water quality indexes may provide the guiding data for sustainable water-resources management in Vietnam DOI: 10.1061/(ASCE)EE.1943-7870.0000314 © 2011 American Society of Civil Engineers CE Database subject headings: Surface water; Pollutants; Water quality; Evaluation; Vietnam Author keywords: Surface water; Water quality indexes; Evaluation; Principal component analysis; Rating curve; Vietnam Introduction Assessment of water quality is very important to human health and a safe environment A water quality index (WQI) is a means of summarizing large amounts of water quality data into simple terms (e.g., good, fair, poor) for reporting to policymakers and the public in a comprehensive, consistent manner [Canadian Council of Ministers of the Environment (CCME) 2001] A water quality index makes information more easily and rapidly interpretable than a list of numerical values The concept of the WQI was first introduced more than 150 years ago in Germany, where the presence or absence of certain organisms in water was used as an indicator of the fitness of a water source (Ott 1978) It is believed that Horton’s index (Horton 1965) started the trend toward using numerical scales to assess water quality Since that time, numerous water quality indexes have been developed and applied throughout the world (Couillard and Lefebvre 1985) In Vietnam, the national surface-water monitoring network was established in 1996 by the Vietnamese Environmental Protection Agency (VEPA) Water quality monitoring data are collected and used for reporting the national environmental status every year However, water quality is evaluated only by comparing individual parameters with the Vietnamese surface-water standard An overall water quality evaluation, as well as water quality comparisons of different monitoring sites both within a region and among different regions, had not yet been conducted This was because no evaluation tool had been implemented The objectives of this study, therefore, are twofold The first objective is to develop water quality indexes for evaluating surface-water quality and identifying water pollutants in Vietnam These indexes can then be used as a tool to communicate about surface-water quality among scientists, decision-makers, and the general public The second objective is to apply the developed WQIs to evaluate, for the first time, the water quality of important water bodies in Vietnam by using the national surface water monitoring data from 1999 to 2007 Materials and Methods Researcher, Dept for Marine Mechanics and Environment, Institute of Mechanics, Hanoi, Vietnam Associate Professor, Dept of Environmental and Occupational Health, National Cheng Kung Univ (NCKU), Tainan City, Taiwan; formerly, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea (corresponding author) E-mail: suthisuthi@gmail.com Senior Lecturer, Faculty of Engineering, Mechanics and Automation, Univ of Engineering and Technology (UET), Vietnam National Univ., Hanoi, Vietnam Professor, School of Environmental Science and Engineering (SESE), Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea Note This manuscript was submitted on August 25, 2009; approved on August 11, 2010; published online on August 12, 2010 Discussion period open until September 1, 2011; separate discussions must be submitted for individual papers This paper is part of the Journal of Environmental Engineering, Vol 137, No 4, April 1, 2011 ©ASCE, ISSN 0733-9372/2011/ 4-273–283/$25.00 Study Area Fig presents the existing national surface-water monitoring network of Vietnam, covering almost 100 stations in 17 provinces The main purpose of this monitoring network is water pollution assessment The monitoring sites include lakes, rivers, and streams, which are mainly in urban locations, near residential areas, or close to factories or industrial zones Twenty-seven water quality parameters have been monitored: pH, dissolved oxygen (DO), water temperature (Tw), turbidity, conductivity, suspended solids (SS), total dissolved solids (TDS), chloride (ClÀ ), biochemical oxygen demand (BOD5 ), chemical oxygen demand (COD), total coliform (T coli), fecal coliform, ammonium-nitrogen (NHỵ -N), nitratenitrogen (NO3 -N), nitrite-nitrogen (NO2 -N), orthophosphatephosphorus (PO3À -P), total phosphorus, oil and grease, heavy JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 / 273 J Environ Eng 2011.137:273-283 index score Principal component analysis (PCA) was applied to divide the selected parameters into groups In this method, the original variables were transformed into new uncorrelated variables, called the principal components (PC) The PC can be expressed as Lang Son Hanoi zij ¼ ai1 x1j þ ai2 x2j þ ai3 x3j þ Á Á Á þ aim xmj Quang Ninh ð1Þ Hai Phong where z = component score; a = component loading; x = measured value of variable; i = component number; j = sample number; and m = total number of variables The number of principal components to remain and their component loadings are characterized by eigenvalues, percent of total variance, and cumulative percentage All of these statistical tests are provided in SPSS 15.0 version for Windows Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved Nghe An Thanh Hoa Statistical Analysis Hue Da Nang DakLak Binh Duong Ho Chi Minh Long An Dong Nai Vung Tau Surface-water quality trends for each province as well as for the whole country over the period studied (1999 to 2007) were analyzed by applying a basic linear regression-based model, with time of year as an independent variable and water quality index as a time-dependent variable and tested by one-way ANOVA To find the forces driving degradation trends in water quality in the provinces studied, Pearson’s correlations between water quality index and population growth, urbanization, and industrialization were determined Urbanization was reflected by the ratio of urban population to total population, and industrialization was reflected by the percentage of industrial-sector gross product of the total gross combined product of industry, agriculture, forestry, and aquaculture All the statistical processes were performed using SPSS 15.0 software for Windows Results and Discussion Tien Giang Can Tho Development of Water Quality Indexes Ca Mau Fig Existing national surface-water quality monitoring network (data from Vietnam Environmental Protection Agency) metals [Iron (Fe), Lead (Pb), Cadmium (Cd), Mercury (Hg), Zinc (Zn), Copper (Cu), Nickel (Ni), Chromium (Cr)], and pesticides Development of Water Quality Indexes Water quality indexes were developed in three steps Step was parameter selection Water quality parameters were set according to the following criteria First, the selected parameters should represent the overall water quality status and reflect each impairment category for freshwater systems (Dunnette 1979), including oxygen status, eutrophication, health aspects, physical characteristics, and dissolved substances Second, they should be included in Vietnam’s surface-water standards, to allow the building of rating curves Third, for utility of the WQI within Vietnam, chosen parameters should be among the national monitoring program’s existing surface-water monitoring parameters Finally, parameters that are most often monitored and have known significant effects on water quality should be selected In step 2, the rating curves method was applied to transform the concentrations of water quality variables into quality scores In step 3, a hybrid aggregation function of additive and multiplicative forms suggested by Liou et al (2004) was used to aggregate subindexes to produce a final Water Quality Parameters Selection Water quality monitoring data show that among 27 parameters, eight parameters (SS, turbidity, DO, COD, BOD5 , PO3À -P, NHỵ -N, and T coli) are the most frequently monitored and important for water quality evaluation because their measured concentrations often exceed the Vietnamese surface-water standards The toxic parameters such as cyanide, heavy metals, phenols, and pesticides are also of concern, although they have been less monitored The monitoring parameters can therefore be divided into two groups The basic group comprising the eight mentioned parameters can be used for the purpose of spatial and temporal water quality comparison as well as identification of water pollutants The additional, less-monitored group, including water Tw, pH, and toxic substances (phenols, pesticides, cyanide, and heavy metals) can provide needed information, especially on toxic pollutants Transforming the Concentrations of Selected Water Quality Parameters into a Common Scale Rating curves for all the water quality variables included in the list of Vietnamese surface-water quality standards were developed The range of water quality parameters and their five key-points defined for rating curves are presented in Table On the basis of these rating curves, parameter concentrations received final scores between (the worst case) and 100 (the best case) The curves are in the piecewise-linear-membership-functions form (Fig 2) The bases of such functions were Vietnam’s national technical regulations on surface-water quality [Ministry of Natural Resources and Environment (MONRE) 2008] and industrial waste water 274 / JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 J Environ Eng 2011.137:273-283 Table Range of Water Quality Parameters and Their Key Points Defined for Rating Curves Score value Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved Parameter pH Temperature DO saturated Turbidity SS COD BOD Ammonium (as N) Nitrite (as N) Nitrate (as N) Orthophosphate (as P) Chlorine Fluorine Cyanide Arsenic Cadmium Lead Chrome (3) Chrome (6) Copper Zinc Ni Total iron Mercury Manganese Oils and grease Phenol E coli or thermotolerant coliform bacteria Total coliform 100 75 50 25 Unit Level Level Level Level Level — °C % NTU mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l mg=l most probable number=100 ml 6–8.5 — 88–112 20 10 0.1 0.01 0.1 250 0.005 0.01 0.005 0.02 0.05 0.01 0.1 0.5 0.1 0.5 0.001 0.1 0.01 0.005 20 6–8.5 — 75–88 112–125 20 30 15 0.2 0.02 0.2 400 1.5 0.01 0.02 0.005 0.02 0.1 0.02 0.2 0.1 0.001 — 0.02 0.005 50 5.5–9 — 50–75 125–150 30 50 30 15 0.5 0.04 10 0.3 600 1.5 0.02 0.05 0.01 0.05 0.5 0.04 0.5 1.5 0.1 1.5 0.001 0.8 0.1 0.01 100 5.5–9 — 20–50 150–200 70 100 50 25 0.05 15 0.5 — 0.02 0.1 0.01 0.05 0.05 0.1 0.002 — 0.3 0.02 200 5.5–9.0 40 < 20 and > 200 100 100 80 50 10 — — — 600 10 0.1 0.1 0.01 0.5 — — 0.5 0.01 — 0.5 — most probable number=100 ml 2,500 5,000 7,500 10,000 — discharge standards [Ministry of Science and Technology (MOST) 2005] The rating curves for turbidity and saturated DO were developed by adopting the classification proposed by Pesce and Wunderlin (2000) and Prati et al (1971) Temperature-dependent saturated DO concentration was calculated by the following empirical formula (Elmore and Hayes 1960): C S ẳ 14:652 0:41022T ỵ 0:0079910T 0:000077774T ð2Þ where Cs = saturated DO concentration (mg=l) and T = water temperature (°C) Five levels of water quality are determined according to the QCVN 08: 2008/BTNMT and TCVN 5945: 2005 as follows (Table 1): Level 1: surface water that can be used for the purpose of domestic water supply; Level 2: surface water that can be used for a source of domestic water supply with appropriate treatments or for protection of aquatic life; Level 3: surface water that can be used for irrigation purposes; Level 4: surface water that can be used for other purposes that need lower water quality such as navigation; Level 5: waste water that can be discharged into the permitted water bodies for further treatment only Aggregation Functions Three components of the basic parameter group were extracted by principal component analysis (Table 2) The first component accounted for 46.56% of total variance, indicating strong positive loadings on BOD5 , COD, NHỵ -N, and PO4 -P, and moderate negative loading on DO, according to the factor classification by Liu et al (2003) (strong, moderate, and weak loadings correspond to absolute loading values of > 0:75, 0.75–0.50, and 0.50–0.30, respectively) High levels of organic matter and nutrients consume large amounts of dissolved oxygen This component can be denoted as organic and nutrients pollution The second component, assigned as particulates pollution, correlated strongly with suspended solids and turbidity, and explained 24.02% of total variance The third component, accounting for 12.54% of total variance, was contributed by T coli only This component is responsible for bacteria pollution The aggregation function for the basic water quality indicator (WQIB ) is therefore proposed as #1=3 " 1X 1X WQIB ẳ q ì q ì qk 3ị i¼1 i j¼1 j where WQIB = basic water quality index; qi = subindex value of the organic and nutrients group containing DO, BOD5 , COD, NHỵ -N, JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 / 275 J Environ Eng 2011.137:273-283 100 100 75 50 75 score value score value score value 75 50 25 0 20 40 60 80 100 120 140 160 180 200 220 20 40 60 80 100 120 75 75 50 25 100 50 25 20 30 40 50 60 70 80 90 75 50 25 0 10 60 70 80 90 100 110 -1 ) Suspended solid (mg L score value 100 score value 100 10 20 30 40 50 Turbidity (NTU) Dissolved oxygen (% saturated) score value 50 25 25 10 15 20 25 30 35 40 45 50 55 -1 -1 10 11 12 -1 BOD (mg L ) COD (mg L ) Ammonium nitrogen (mg L ) 100 100 score value 75 score value Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved 100 50 25 75 50 25 0 0.1 0.2 0.3 0.4 0.5 -1 Orthophosphate (mg L ) 0.6 2500 5000 7500 10000 12500 Total coliform (most probable number/100ml) Fig Assigned rating curves for the studied water quality variables and PO3À -P; qj = subindex value of the particulates group containing SS and turbidity; and qk = subindex value of the bacteria group containing only T coli Both the basic parameter and additional parameter groups were used to form the overall water quality index (WQIO ) The subindexes for additional water quality parameters were first calculated Each subindex then was compared with the WQIB and taken into account only if it was lower The Tw and pH coefficients were calculated directly from their respective subindexes The toxic coefficient was calculated by averaging all scores of toxic substances (Tables and 4) Since the WQIO values were scaled between and 100, the Tw, pH, and toxic coefficients were scaled between 0.01 and The WQIO aggregation function is therefore proposed as #1=3 Y 1=n " X n 1X WQIO ẳ Ci q ì q ì qk 4ị iẳ1 i jẳ1 j Table Component Matrix, Eigenvalues, and Accumulative Percentages for the Extracted Principal Components Loading of variables DO Turb SS BOD5 COD T coli NHỵ -N PO3 -P Eigenvalues Percentage of total variance Cumulative percentage 276 / JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 J Environ Eng 2011.137:273-283 PC1 PC2 PC3 À0:713 0.067 0.104 0.929 0.912 0.073 0.798 0.929 3.724 46.56 46.56 0.079 0.979 0.975 À0:040 À0:002 0.009 À0:066 À0:022 1.922 24.02 70.58 À0:015 0.017 À0:024 À0:061 À0:059 0.994 0.074 À0:033 1.003 12.54 83.12 Table Example of WQIB and WQIO Calculation for the Red River Sample P Parameter Concentration Subindex score 1=5ị 5iẳ1 qi Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved (1) (2) DO (mg=l) DO saturated (mg=l) Percentage of DO saturated BOD5 (mg=l) COD (mg=l) PO34 -P (mg=l) NHỵ -N (mg=l) SS (mg=l) Turbidity (NTU) T coli (#=100 ml) pH Tw (°C) Cd (mg=l) Pb (mg=l) Fe (mg=l) a (3) 5.03 7.65 65.74 7.58 9.88 0.095 0.047 17 16.9 550 7.9 28.5 0.008 0.059 1.22 1=2ị (4) P2 jẳ1 qj (5) qk WQIB Ci WQIO (6) (7) (8) (9) 87.27 90.05 100 92.28 61.01 56.30 P5 Column (4): 1=5ị iẳ1 qi ẳ 65:74 ỵ 70 ỵ 100 ỵ 100 ỵ 100ị=5 ẳ 87:27 Column (5): ð1=2Þ 65.74 70.60 100 100 100 100 80.11 100 100 100 70.00 49.02 64.00 P2 jẳ1 qj ẳ 80:11 ỵ 100ị=2 ẳ 90:05 Column (6): qk ẳ 100 Column (7): WQIB ẳ ẵ1=5ị P5 iẳ1 qi ì 1=2ị P2 jẳ1 qj ì qk 1=3 ẳ 92:28 Q Column (8): n1 C i ị1=n ẳ ẵ1=100ị ì 70 ỵ 49:2 ỵ 64ị=31 ẳ 0:61a Column (9): WQIO ẳ Qn Ci ị1=n ì WQIB ẳ 0:61 ì 92:28 ẳ 56:30 Because only Cd, Pb, and Fe subindex scores were lower than WQIB , they are further used to calculate I O Table Example of WQI Calculation Results Report Sample description Location Red River Index Critical parameter Time Basic Overall Name Concentration Subindex Water quality 23/4/2002 92.28 56.30 Pb (mg=l) 0.059 49.02 Fair where C i = coefficients addressing the subindexes of Tw, pH, and toxic substances; and n = number of coefficients Water quality then can be classified on the basis of the WQIB or WQIO score as follows: 91 to 100 is excellent water quality, 76 to 90 is good water quality, 51 to 75 is fair, 26 to 50 is marginal, and to 25 is poor water quality Application of the Water Quality Indexes to National Water Monitoring Data Evaluation of Water Quality The WQIB was calculated for all 3,425 samples taken from 98 sampling stations from 1999 to 2007 In northern Vietnam, there are 24 monitoring sites in four provinces (Lang Son, Quang Ninh, Hai Phong, and Ha Noi) Calculated WQIB values show only one sampling site (4.17% of total sites) classified as good, whereas eight sites (33.33%) have poor water quality Water quality in particular represents the sampling sites’ geographic locations Severe pollution in the Hanoi and Lang Son drainage systems reveals the impacts of municipal and industrial wastewater on water quality The West Lake located in inner Hanoi was an exception because of the self purification of a very large water body (more than 500 ha) ranked as having fair water quality Fair to good water quality was detected in the Ky Cung River’s sites in the suburb of Lang Son Furthermore, WQIB can help identify water pollutants Fig presents the absolute and relative scores of three subcategories (bacteria, particulates, and organics and nutrients) in the WQIB calculated for northern Vietnam In this figure, the relative scores (presented by percentages) can be interpreted such as the lower the score for a group, the more heavily water is polluted by that group It is found that drainage systems in inner Hanoi and Lang Son were severely polluted by organic matter and nutrients as well as bacteria (scoring 1.1–7.09 and 1.0–17.56, respectively) Lakes located in inner Hanoi, Hai Phong, and Lang Son were classified as poor to moderate in quality on organics and nutrients (scoring 19.37– 42.60) and marginal to fair on bacteria (scoring 36.18–72.46) and particulates (47.37–67.83) The main problem with rivers’ water quality (except the Ky Cung River) however, was particulates, ranked as very poor to moderate in quality (scoring 6.45–42.29) Organic matter and nutrients (scoring 52.29–71.30) and bacteria (50.90–100) were not a big concern The Ky Cung River (Lang Son Province), classified as the most clean among the monitored water bodies in northern Vietnam, had fair to relatively good conditions for all three subcategories (scoring 60.58–90.22) In the central part of Vietnam, five provinces/cities (Thanh Hoa, Vinh, Hue, Da Nang, and Daklak) with a total of 24 sites were monitored for surface-water quality The WQIB shows water quality mainly ranked as marginal at 66.67% of the sampling sites Water quality in Da Nang and Daklak was worse than in other provinces A breakdown of three water quality subcategories in central Vietnam is presented in Fig The main pollutant factor was bacteria for these two provinces’ water bodies, scoring 21.11–37.81 in Da Nang and 7.43–40.70 in Daklak Among the central provinces, Hue had the highest surface-water quality (scoring 68:24 Æ 22:33) Huong River water quality (scoring 69.15–76.34) was much better than that of other water bodies in Hue city Lakes and rivers located in inner Hue were polluted either by bacteria (scoring 26.0 in the An Cuu River) or by organic matter and nutrients (scoring 34.8 in Tinh Tam Lake) Water quality in Thanh Hoa and Vinh was classified from marginal to fair Better scores were obtained from large rivers outside cities, such as the Ma River in Thanh Hoa (scoring 63.45), the Dao Cua Tien River JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 / 277 J Environ Eng 2011.137:273-283 Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved Fig Identification of pollutants contributing to water pollution in the northern part of Vietnam, 1999–2007 (absolute and relative scores of bacteria, particulates, and organic and nutrients groups) (58.11), and the Lam (70.38) in Vinh Other water bodies in the inner cities, however, were in relatively poor condition for bacteria (Cua Nam Lake scoring 17.73) and organic matter and nutrients (36.21 for Thanh Lake) Fifty sampling sites in eight provinces (Ho Chi Minh, Vung Tau, Binh Duong, Can Tho, Dong Nai, Long An, Tien Giang, and Ca Mau) located in the southern economic development zone of Vietnam were included in the national surface-water monitoring network Information on the contribution of these eight provinces to the national economy is presented in Table Ho Chi Minh City, Binh Duong, and Dong Nai are among the most industrially developed provinces in the country The provinces of Vung Tau, 278 / JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 J Environ Eng 2011.137:273-283 Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved Fig Identification of pollutants contributing to water pollution in the central part of Vietnam, 1999–2007 (absolute and relative scores of bacteria, particulates, and organic and nutrients groups) Can Tho, Long An, Tien Giang, and Ca Mau, on the other hand, are among the most developed for agriculture and aquaculture Moreover, population growth rates have been very high in these eight provinces (especially in Binh Duong, at 4:48% yearÀ1 , and Ho Chi Minh City at 2:84% yearÀ1 ), with an average of 2% yearÀ1 (the growth rate of the whole country is 1:33% yearÀ1 ) [Vietnam General Statistical Office (VGSO) 2007] Great pressure for socioeconomic development may result in a deterioration of water quality of this region The WQIB shows 30 sites (60%) classified with poor water quality Extremely poor water quality was detected in the drainage canal and river sites close to residential areas of Ho Chi Minh City (WQIB ranging from 6.45 to 18.5), JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 / 279 J Environ Eng 2011.137:273-283 Table Contribution of the Eight Studied Provinces in the Southern Part of Vietnam to the National Economy Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved Contribution to gross product of Vietnam (%) Economic sector 1999 2000 2001 2002 2003 2004 2005 2006 2007 Industry (8 provinces) Industry (BD, DN, HCM) Agriculture (8 provinces) Agriculture (CM, CT, LA, TG, VT) Aquaculture (8 provinces) Aquaculture (CM, CT, LA, TG, VT) Forestry (8 provinces) 53.69 36.16 17.32 11.79 25.67 23.24 10.92 53.00 36.17 16.95 11.34 26.36 24.22 10.16 52.63 36.77 15.84 10.33 27.66 25.34 10.64 51.45 36.99 15.83 10.58 27.04 24.64 10.38 51.14 37.15 15.82 10.29 27.03 24.36 10.03 51.24 37.68 15.62 10.16 26.86 24.29 10.25 51.23 38.18 15.79 10.24 27.99 25.69 10.29 50.70 37.97 15.47 9.90 27.32 25.03 10.31 49.77 38.19 15.64 7.80 26.51 24.50 10.14 Source: VGSO 2007 Note: BD: Binh Duong Province, DN: Dong Nai Province, HCM: Ho Chi Minh City, CM: Ca Mau Province, CT: Can Tho City, LA: Long An Province, TG: Tien Giang Province, VT: Vung Tau City Ca Mau (7.16–12.22), Tien Giang (11.04–21.62), Can Tho (12.44– 15.91), Binh Duong (14.61–22.96), and Long An (18.42–21.49) The main pollution problems at these sites were from bacteria (scores from to 8.93), rather than particulates and organic matter and nutrients (Fig 5) The remaining 20 sites in the southern part were further classified into a marginal group (12 sites À24%), a fair group (5 sites À10%), and a good water quality group (3 sites À6%) Socioeconomic Development and Water Quality Trends Table gives the summary of trend analysis results of national surface-water quality data for each province as well as for the whole country The results show that water quality over the whole country deteriorated during the period from 1999 to 2007 (slope ¼ À2:69 scores yearÀ1 , p ¼ 0:0001) This decreasing trend can be also found in Hanoi, Hai Phong, Da Nang, Daklak, Ho Chi Minh, Vung Tau, Binh Duong, and Dong Nai cities/provinces (slope ¼ À2:31 to À5:75 scores yearÀ1 , p < 0:05) The existing national monitoring network was designed primarily for the purpose of water quality impact assessment Therefore, the selected monitored cities/provinces are mostly located in the northern, central, and southern economic development regions Most of the water samples were taken from the water bodies receiving discharge from municipal and/or industrial waste water sources Significant (p < 0:05) negative correlations between WQIB and population growth, industrialization, and urbanization were found in the cities/provinces with surface-water quality degradation trends (Table 7) In Hanoi, there were good to excellent negative correlations between WQIB and population growth (R ¼ À0:87), industrialization (R ¼ À0:88), and urbanization (R ¼ À0:9) In Haiphong, fair negative correlations between WQIB and population growth (R ¼ À0:79) and industrialization (R ¼ À0:73) were found Da Nang and Daklak are considered the most economically developed provinces in the central and central highlands parts of Vietnam Surface-water degradation trends there may be the result of rapid population growth as well as industrialization Statistical data from 1999 to 2007 (VGSO 2007) show that population growth rates in Da Nang (2% yearÀ1 ) and Daklak (2:25% yearÀ1 ) were much higher than in other central provinces (Hue had 1:33% yearÀ1 , Thanh Hoa 0:78% yearÀ1 ), and in the country overall (1:33% yearÀ1 ) In the southern part of Vietnam, significant good to excellent negative correlations between WQIB and rapid population growth, urbanization, and industrialization clearly indicate the relationship between water quality degradation and human activities in the provinces of Ho Chi Minh, Vung Tau, Binh Duong, and Dong Nai Worse water quality deterioration was found in Binh Duong Province, where population and industrialization increased 4.48% and 29:99% yearÀ1 during the study period These growth rates are the highest in Vietnam Population growth rates for Ho Chi Minh, Dong Nai, and Vung Tau were 2.84, 1.51, and 2:06% yearÀ1 , respectively, all higher than for Vietnam as a whole (1:33% yearÀ1 ) The industrial growth rate was relatively high in Dong Nai Province (20:01% yearÀ1 ) compared with the whole country (16:46% yearÀ1 ) Application of the Overall Water Quality Index to National Water Monitoring Data Sixty-nine samples of the northern part were calculated for WQIO because of the availability of additional water-quality-parameter monitoring data The additional parameters were Tw (ranged from 14.6 to 33.8°C), pH (6.33–9.28), Cd (0:003–0:08 mg=l), Pb (0:005–0:239 mg=l), and Fe (0:04–5:58 mg=l) The results (Table 8) reveal that water samples were extremely polluted by Cd (50.72% samples with a score equal to 1), marginally polluted by Pb (75.36% samples), and barely polluted from Fe (97.19% of samples ranked from fair to excellent) Because of heavy metals and pH, WQIO scores were significantly lower than WQIB The results show that the WQIB scores ranged from 3.31 to 92.28, proportionally being 40.58, 17.39, and 2.89% of fair, good, and excellent water quality, respectively, whereas WQIO scores ranged from 0.03 to 63.71, with only 8.70% being fair water quality The application of WQIO demonstrates its important role in water pollution evaluation, especially when toxic substances are of concern Surface Water Management and WQI Applications in Vietnam The current national surface-water monitoring network in Vietnam was established for 17 provinces in 1996 by VEPA This limited system was primarily for impact assessment at selected locations, with collected samples tested against national standards Recently, Vietnam’s government has authorized a master plan for a comprehensive environmental monitoring network by the year 2020 (known as Decision 16/2007/QD-TTg) According to this plan, the surface-water monitoring network will cover all of Vietnam’s 64 provinces There will be 414 monitoring sites, a major increase from the present 98 sites Among them are to be 66 sites for basic surface-water quality monitoring and 348 sites assigned to pollution impact assessment (Fig 6) Additional data will arrive from the provincial level monitoring network and environmental projects Monitoring engenders vast data; the challenge of optimizing its use is met by effective tools to easily and rapidly interpret large amounts of water quality data into understandable 280 / JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 J Environ Eng 2011.137:273-283 Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved Fig Identification of pollutants contributing to water pollution in the southern part of Vietnam, 1999–2007 (absolute and relative scores of bacteria, particulates, and organic and nutrients groups) JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 / 281 J Environ Eng 2011.137:273-283 Table Summary of Trend Analysis for National Surface-Water Quality Data, 1999–2007 Trend Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved City/province Northern part Lang Son (LS) Ha Long (HL) Hai Phong (HP) Hanoi (HN) Hanoi drainage system (HN) Central part Thanh Hoa (TH) Vinh (V) Hue (H) Danang (DN) Daklak (DL) Southern part Ho Chi Minh (HCM) Vung Tau (VT) Binh Duong (BD) Can Tho (CT) Dong Nai (Dnai) Long An (LA) Tien Giang (TG) Ca Mau (CM) Whole country Number of monitoring stations Number of observations 24 24 4 5 50 10 5 5 98 746 60 41 232 241 172 765 48 169 210 155 183 1914 389 106 202 260 83 432 256 186 3425 Basic water quality index (WQIB ) (mean Ỉ S:D:) 53:45 Ỉ 30:26 41:25 Ỉ 20:04 32:50 Ỉ 22:25 46:65 Ỉ 25:55 3:25 Ỉ 2:48 49:57 Æ 29:17 58:13 Æ 25:88 68:24 Æ 22:33 41:99 Æ 29:98 36:94 Ỉ 30:29 18:49 Ỉ 20:45 49:98 Ỉ 32:09 35:37 Ỉ 29:57 18:63 Ỉ 17:02 44:91 Ỉ 31:87 36:01 Æ 26:80 19:12 Æ 17:05 11:53 Æ 10:18 33:53 Æ 29:03 Slope (scores=year) p value À0:33 0.148 0.037 0.023 0.323 0.005 À4:82 À4:71 0.064 0.661 0.057 0.011 0.013 À5:75 À2:31 À2:44 À5:16 À5:73 0.031 0.001 0.001 0.061 0.035 0.481 0.059 0.72 0.0001 À4:26 À2:69 Table Pearson’s Correlations between Surface-Water Quality (WQIB ) and Population Growth, Urbanization, and Industrialization, 1999–2007 Correlation (p value) Province Lang Son Hai Phong Hanoi Thanh Hoa Hue Da Nang Daklak Ho Chi Minh Vung Tau Binh Duong Can Tho Dong Nai Long An Tien Giang Ca Mau Whole country a Population growth Urbanization 0.978 (0.134) À0:790a (0.020) À0:866b (0.005) À0:771 (0.229) À0:649 (0.082) À0:853b (0.007) À0:846b (0.008) À0:705 (0.051) À0:929b (0.001) À0:903b (0.002) À0:695 (0.055) À0:755a (0.030) À0:386 (0.345) À0:656 (0.077) À0:143 (0.736) À0:962b (10.30E-04) 0.998 (0.057) À0:554 (0.154) À0:900b (0.002) À0:431 (0.569) À0:266 (0.524) À0:517 (0.189) À0:138 (0.745) À0:588 (0.125) À0:799a (0.017) 0.895b (0.003) À0:562 (0.147) 0.143 (0.735) À0:565 (0.145) À0:664 (0.072) À0:212 (0.614) À0:951b (20.90E-04) Industrialization 0.942 (0.217) À0:729a (0.040) À0:882b (0.004) À0:921 (0.079) À0:656 (0.077) À0:790a (0.020) À0:600 (0.116) À0:817a (0.013) 0.329 (0.427) À0:972b (0.000) À0:762a (0.028) À0:704a (0.041) À0:067 (0.876) À0:489 (0.219) À0:064 (0.880) À0:966b (90.69E-05) Correlation is significant at the 0.05 level (2-tailed) Correlation is significant at the 0.01 level (2-tailed) b information on surface-water conditions for policymakers and the public, who all have a stake, as well as water-management professionals The two newly developed water quality indexes can serve as such tools The WQIB can be effectively used to evaluate the spatial and temporal variations of surface-water quality, to identify water pollutants, and to reflect the impacts of socioeconomic development on surface-water quality The WQIO can provide additional information, particularly on toxic substances contributing to water pollution Together the indexes can well serve the objective of informing policy decisions for sustainable water-resources management in Vietnam 282 / JOURNAL OF ENVIRONMENTAL ENGINEERING © ASCE / APRIL 2011 J Environ Eng 2011.137:273-283 Table Overall Water Quality Index (I O ) for National Water Quality Monitoring Data Percentage of samples assigned to each water quality level Score (rank) Tw Downloaded from ascelibrary.org by Florida International University on 09/26/13 Copyright ASCE For personal use only; all rights reserved 91–100 (excellent) 100 76–90 (good) 51–75 (fair) 26–50 (marginal) < 25 (poor) pH Cd Pb Fe IB 98.55 2.9 21.74 24.64 4.35 88.41 4.35 4.35 2.90 17.39 40.58 2.90 39.13 1.45 50.72 20.29 75.36 IO 8.70 37.68 53.62 The WQIO can provide additional information, especially on the contribution of toxic substances to water pollution Surface-water quality in the northern and central parts was poor, containing organic matter, nutrients, and bacteria, whereas water in the southern part was primarily polluted by bacteria Drainage systems, lakes and stretches of rivers close to urban areas had extremely poor water quality This raises alarms about the impacts of discharging untreated wastewater on the quality of surface water in big cities Analysis of water quality trends shows some possible negative impacts of socioeconomic development on surface-water quality in the provinces studied The implementation of water quality indexes can well serve the objective of sustainable water-resources management in Vietnam Acknowledgments The writers thank the Centre for Environmental Monitoring Data and Information, Vietnam Environmental Protection Agency, for providing the national surface water monitoring data This research project was funded by Asia-Pacific Network for Global Change Research (ARCP2009-13NMY-STHIANNOPKAO) and International Environmental Research Center (IERC), Republic of Korea References Fig Proposed national surface-water quality monitoring network in the year 2020 (data from Vietnam Environmental Protection Agency) Conclusions Two types of water quality indexes were developed for the purpose of surface-water quality evaluation in Vietnam The WQIB can be effectively used to evaluate the spatial and temporal variations in surface-water quality as well as to identify water pollutants Canadian Council of Ministers of the Environment (CCME) (2001) “Canadian water quality guide-lines for the protection of aquatic life: CCME water quality 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calculated for all 3,425... impacts of discharging untreated wastewater on the quality of surface water in big cities Analysis of water quality trends shows some possible negative impacts of socioeconomic development on surface -water. .. types of water quality indexes were developed for the purpose of surface -water quality evaluation in Vietnam The WQIB can be effectively used to evaluate the spatial and temporal variations in surface- water