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Surface Water Quality Assessment Using Multivariate

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Surface Water Quality Assessment Using Multivariate 8-10 September 2014- Istanbul, Turkey 578 Proceedings of SOCIOINT14- International Conference on Social Sciences and Humanities SURFACE WATER QUALITY ASSESSMENT USING MULTIVARIATE STATISTICAL TECHNIQUES (CASE STUDY: TALAR RIVER, IRAN) Kaka Shahedi *1, Alireza Kaveh2, Mahmoud Habibnejad3, Jamshid Ghorbani4 1Assistant Professor, Department of Watershed Management, Sari Agricultural Sciences and Natural Resources University, Iran. ([email protected]) 2 M.Sc., Department of Watershed Management, Sari Agricultural Sciences and Natural Resources University, Iran. 3Professor, Department of Watershed Management, Sari Agricultural Sciences and Natural Resources University, Iran. 4Associate Professor, Department of Rangeland Management, Sari Agricultural Sciences and Natural Resources University, Iran. *Corresponding author Abstract In this study, spatio-temporal variation of surface water quality were assessed in Talar River, located in north of Iran based on 12 parameters at six stations during 2003-2011 using one-way ANOVA, principal component analysis (PCA) and cluster analysis (CA) techniques. The results of one-way ANOVA showed that temporal and spatial variations influences on water quality parameters siginificantly as decline in river water quality. Based on this analysis, Khatirkuh-Doab and Pol Shahpoor stations had the highest and the lowest amounts of almost all of the water quality parameters, respectively. The results of principal component analysis indicated a close relationship between the anions and cations, concentration of soluble salts, electric conductivity and total hardness in all years of study and at all stations. Moreover, PH and HCO3 parameters in 2005-2006, 2007-2008, 2008-2009 and 2010-2011 and at Kiakola, Pol Shahpour and Shirgah–Talar stations; Cl, Na and SAR parameters at Paland station; Total Hardness and SO4 parameters at Kiakola station and HCO3 and PH parameters at Kiakola, Pol Shahpour and Shirgah-Talar stations had a close relationship with each other. Mg parameter at Pol Shahpour station, SO4 parameter at Khatirkuh-Doab station, HCO3 parameter at Pol Sefied-Talar and Khatirkuh-Doab stations, PH parameter at Pol Sefid-Talar, Khtirkuh-Doab, and Palnd stations had a significant presence in 2003-2004, 2004-2005, and 2009-2010. Cluster analysis results also showed that Kiakola and Shirgah – Talar stations are placed in the first cluster, Pol Shahpour and Paland stations are set in the second cluster, Khatirkuh-Doab and Pol Sefied–Talar stations are located in the third and fourth clusters, respectively. Keywords: Principal Component Analysis, Cluster Analysis, Talar River, Water Quality, Iran. 1. INTRODUCTION Surface waters have the highest risk of infection due to easy access to sewage disposal (Samarghandi et al., 2007). Among surface water resources, rivers are the most vulnerable water bodies because of carrying urban and industrial wastewaters and agricultural drainage (Singh et al., 2005; Wang and Xiao, 2007). In addition to contaminant matter, factors such as increasing in water demand, higher living standards and reducing acceptable water supplies caused unsuitable social and environmental situations around the world (Kerachian and Karamouz, 2006). Therefore, assessment of water quality due to its direct impact on public health and aquatic marine life is important (Dixon and Chriswell, 1996). Data which describe the spatio-temporal variations of water quality in a river could be used to represent the relative importance of natural and human impacts (Markich and Brown, 1998) and could provide dynamicinformation for decision makers in water resources management (Xu et al., 2012). This requires a better understanding of spatio-temporal variations of water systems pollution (Bu et al., 2010). In recent years, multivariate analysis such as Principal Component Analysis (PCA), Cluster Analysis (CA) and also univariate analysis such as one-way ANOVA have been used to better assess the spatio-temporal variations of water quality parameters (Reghunath et al., 2002; Deano et al., 2008; Saidmuhammad et al., ISBN: 978-605-64453-1-6 8-10 September 2014- Istanbul, Turkey 579 Proceedings of SOCIOINT14- International Conference on Social Sciences and Humanities 2010; Varol et al., 2012; Fan et al., 2013). These techniques help to better understand the spatio-temporal variations in water quality and provide an effective means for the actual management of water resources (Varol and Sen, 2009; Zhang et al., 2009; Li and Zhang, 2010). This study is carried out in Talar Watershed located in Mazandaran province, north of Iran. This Watershed provides 92 MCM of water that is used for agriculture (Nazari, 2010) and its water quality is average to good for drinking (Asadi and Fazloula, 2011). Main objective of this study is to investigate the spatio-temporal variations of water quality parameters in this watershed using a combination of multivariate and univariate techniques. Also, we used AHP technique to find the main source of pollution. 2. METHODOLOGY 2.1. Study area Talar Watershed is located between 35° 44' 41" to 36° 19' 13" East longitude and 52° 35' 38" to 53° 23' 56" North latitude which is drained by a main river named Talar River (Nazari, 2010). Six stations (Kiakola, PolShahpour, Shirgah-Talar, PolSefied-Talar, Khatirkuh-Doab and Paland) were chosen for this study (Fig 1). Fig.1. Geographical location of Iran, Mazandaran Province, Talar Watershed and stations 2.2. Data analysis A set of 12 water quality parameters including Salt Concentration (TDS), Electrical Conductivity (EC), acidity (pH), Cations (Ca, Mg, Na and K), Anions (HCO3, CL and SO4), Sodium Absorption Ratio (SAR) and Total Hardness (TH) at 6 ststions were analyzed on a monthly basis. These parameters were measured during 2003-2011. The spatio-temporal variations of river water quality parameters were assessed by one-way analysis of variance using SPSS software. For any significant effect the mean values were compared using Duncan test. Then, using STATISTICA software and Principal Component Analysis (PCA) the spatio- temporal variations of water quality parameters were analyzed. So, using the PC-ORD software and Cluster Analysis (CA), water quality monitoring stations of Talar watershed were clustered. Finally, using the Expert Choice software and Analytic Hierarchical Process (AHP) technique based on the questionnaire filled by experts, the relative importance of pollution sources (lithology, land use change, landuse type and mining of river bed) in the study area was determined. 3. RESULTS 3.1. Spatial variations of water quality The results of the one-way ANOVA on water quality parameters showed a significant effect of spatial variations on all parameters variations during the study period (Table 1). The results showed that Khatirkuh- Doab (upper part of the watershed) and Pol Shahpour (lower part of the watershed) stations had the highest and lowest amount of prameters, respectively (Figs 2 and 3). Spatial analysis revealed that among 12 mentioned components at Kiakola, Pol Shahpour and Pol Sefied- Talar stations, three first components and at Shirgah-Talar and Khatirkuh-Doab stations two and four first components, respectively, represent the spatial variations of water quality (Tables 2 and 3). ISBN: 978-605-64453-1-6 8-10 September 2014- Istanbul, Turkey 580 Proceedings of SOCIOINT14- International Conference on Social Sciences and Humanities Table1. Results of ANOVA for spatial response of water quality parameters in Talar watershed Parameters F TDS 428.03*** EC 433.4*** pH 5.16*** *** HCO3 22.64 CL 312.13*** *** SO4 295.75 Ca 218.48*** Mg 204.42*** Na 322.96*** K 243.49*** SAR 118.25*** Hardness 2.56*** (***significant at the level of 0.001 ≥ P) 1400 2000 a 1800 1200 a 1600 b 1000 b 1400 800 1200 TDS (mg/l) EC 1000 c (mmhos/cm) d c 600 d 800 400 e 600 f e f 400 f 200 200 0 0 5 7,9 4,5 a a b b 4 b b 7,88 ab 3,5 c 7,86 HCO3(me/l) 3 7,84 bc 2,5 pH (mg/l) bc 7,82 2 c 1,5 7,8 c 1 7,78 0,5 7,76 0 7,74 ISBN: 978-605-64453-1-6 8-10 September 2014- Istanbul, Turkey 581 Proceedings of SOCIOINT14- International Conference on Social Sciences and Humanities 8 7 a 7 a 6 6 5 b 5 b 4 SO4 (me/l) 4 Cl (me/l) 3 c 3 c 2 2 d d e 1 1 e e e 0 0 Fig.2. Spatial variations of water quality parameters in different stations in Talar Watershed 4,5 a 8 a 4 7 b 3,5 6 b 3 5 c Ca (me/l) 2,5 c Mg (me/l) d 4 c 2 e d 3 e 1,5 f 2 1 1 0,5 0 0 7 0,12 a a 6 0,1 b 5 b 0,08 c 4 K (me/l) d Na (me/l) 0,06 3 c e 2 d c 0,04 f d 1 e e 0,02 e 0 0 ISBN: 978-605-64453-1-6 8-10 September 2014- Istanbul, Turkey 582 Proceedings of SOCIOINT14- International Conference on Social Sciences and Humanities 700 a 600 3 a a 500 ab 2,5 b TH (mg/l) 400 b 2 b SAR (me/l) 300 1,5 c b c 200 1 100 0,5 d d 0 0 Fig.3. Spatial variations of water quality parameters in different stations in Talar Watershed Table 2.Percentage of expressed spatial variations for main components in Talar Watershed Component are expressed as precentage variation Components Kiakola PolShapour Shirghah-Talar Polsefied-Talar Khatirkuh-Doab Paland 1 51.21 63.66 68.80 62.94 50.08 43.90 2 19 12.63 13.05 11.38 14.70 18.54 3 12.75 8.85 7.40 8.67 11.02 14.10 4 7.62 7.57 6.19 8 10.51 8.04 5 4.44 3.82 2.85 4.22 5.67 7.76 6 2.94 2.61 1 3.29 0.51 3.31 7 1.02 0.69 0.71 1.38 2.83 2.82 8 0.76 0.13 0.1 0.06 1.48 1.30 9 0.21 0.02 0.05 0.05 0.11 0.21 10 0.02 0.02 0.02 0.01 0.06 0.02 11 0.01 0.00 0.02 0.01 0.03 0.01 12 0.00 0.00 0.00 0.00 0.01 0.00 Table 3.Comparison of water quality parameters for main components in Talar Watershed Stations Kiakola PolShapour Shirghah- Polsefied-Talar Khatirkuh-Doab Paland Talar Compon ents 1 2 3 1 2 3 1 2 1 2 3 1 2 3 4 1 2 3 - TDS -0.28 0.01 -0.98 -0.12 0.02 -0.99 0.01 -0.99 0.01 0.05 -0.97 0.15 0.07 -0.04 0.91 0.
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