An Integrated Study to Investigate the Water Quality of Ramganga River, Ganga Basin, India

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1 An Integrated Study to Investigate the Water Quality of Ramganga River, Ganga Basin, India M.Y.A. Khan*, S. Daityari *, K. Muzamil ** & G. J. Chakrapani * * Department of Earth Sciences, Indian Institute of Technology Roorkee, Roorkee , India ( myawar.akhan@gmail.com) ** Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee , India Abstract In India, water pollution has been a significant problem. Major Himalayan Rivers flowing through India have also been affected by this problem, leading to poor water quality and the inability to use river water for domestic as well as industrial purposes. Ramganga River, the first major tributary of river Ganga, has faced water quality problems as it flows through important industrial areas of the states of Uttarakhand and Uttar Pradesh. In this study, the spatial variation of water quality along the total stretch of the river was analyzed, which includes various physiochemical characteristics. This takes into consideration the physical and chemical characteristics, including heavy metals. A correlation matrix was formed, followed by PCA analysis to evaluate the data accuracy. The data was credible, accurate and the result was then compared to existing WHO guidelines. Keywords Ramganga River, water quality, correlation matrix, PCA INTRODUCTION Water flowing through streams, springs, creeks and rivers constitutes surface water forming ponds, lakes and oceans (Manahan, 1993). However, the quality of surface water has been degrading with time. Rivers flowing through major industrial and populous areas carry a large amount of industrial and municipal waste and agricultural runoff in their huge catchment area. The water quality in an area is also affected by natural (erosion, precipitation, and weathering) and anthropogenic processes (agricultural and industrial activities, water discharge) (Carpenter et al., 1998; Jarvie et al., 1998). Poor water quality contributes to crop wreckage, food waste and other degradable waste (Finnveden et al., 2009), including fecal matter of humans and animals (Stoate et al., 2009). Nutrients like phosphorus and nitrogen contributed by fertilizers aid the growth of phytoplankton, leading to eutrophication. Knowledge about river water quality thus, would help while planning river water management. Monitoring the quality of river water by understanding the physiochemical and biological characteristics can help reduce the complexity in interpretation of water quality due to spatial variations (Dixon and Chiswell, 1996). Effective water management is possible by identifying possible sources of pollution by employing multivariate statistical techniques on large matrix data (Lee et al., 2001; Adams et al., 2001). This has been used in the past to identify natural and anthropogenic sources of pollution in surface water bodies (Singh et al., 2004, 2005). This study aims to evaluate the spatial distribution of water quality in Ramganga River along its whole stretch. The main intentions of the study were to make an organized appraisal and

2 estimation of river pollution under the influence of high incursion of metal pollutants from anthropogenic activities. STUDY AREA AND GEOLOGY Ramganga River is one of the major tributaries of Ganga River and it originates from the Dudhotali ranges of Gairsain village of district Chamoli in Kumaon Himalayas. The total stretch of Ramganga river from its origin to its end is 642 Km lies in 30 o N to 27 o N and 79 o E to 79 o E with the total catchment area of about 32,493 km 2 and mean elevation of 1530 m from mean sea level. The main attractive feature of this river is its flowing patterns, in upstream its covers the Kumaon Himalayas including Jim Corbett National Park in Uttarakhand while in downstream of its course it flows through the highly industrialized district of Uttar Pradesh. After flowing more than 400 Km in Ganga Plains, River Ramganga finally meets Ganga River in district Farrukhabad of Uttar Pradesh. Figure 1: Ramganga River catchment In the middle and outer Himalayan ranges, it is a horseshoe shaped structure comprising of mountainous terrains while in South of Himalayan ranges, a portion of the catchment encompasses the Siwalik Hills. The catchment is characterized by steep hills, deep and narrow valleys (CWC, 2012). Ramganga River constitutes two major lithotectonic zones in Kumaon Himalayas which are Sub- Himalayas and Lesser Himalayas (Gupta and Joshi, 1990). While in Ganga Plains the river comprises of lithostratigraphic sequence of Varanasi Older Alluvium, Ganga/Ramganga Terrace

3 Alluvium and Ganga/Ramganga Recent Alluvium, the latter two constitute the Newer Alluvium (Khan and Rawat, 1990). SAMPLE COLLECTION AND ANALYSIS The collection of water samples was done in pre monsoon season of 2014 from the whole stretch of Ramganga River covering distance of 642 Km. A total of 16 water samples were collected and the bottles in which the samples were collected were treated with 2% of nitric acid and at the time of collecting samples bottles were rinsed two times with the river water to avoid contamination. The sampling location network was planned to cover broad range of determinants at key sites. The preservation and analysis of samples were done as per the procedure given in APHA, Standard Methods for the Examination of Water and Wastewater, 20th ed. (1998). RESULTS AND DISCUSSION The physico-chemical parameters that were observed in this study were subject to statistical analysis and compared to their WHO recommended values (as shown in Table). A crucial role is played by Temperature in a riverine system. Temperature affects the solubility of salts, dissolved oxygen, biodegradation rate and other physico-chemical parameters (Rao and Rao, 2010). It has a strong effect on aquatic life as well. For instance, a temperature change can trigger photosynthesis by aquatic plants. The temperature range was 25.2 to 31.1 o C, which is close to the WHO recommendations of RG1 and RG 14 showed the lowest and highest temperatures, respectively. In general, an increase in temperature was observed as we moved downstream. This change in temperature is attributed to the drop of elevation from the mean sea level of the sampling points RG1 (starting point) being in the Himalayas and RG14 in the Ganga flood plains. It could also be due to increasing solar radiation as the sampling was carried out in the morning at RG1 through noon at RG16. The ph values ranged from 6.54 to 7.94, which mean that the river water ranged from slightly acidic to slightly alkaline. The alkaline nature could be a result of the carbonate rocks in the area like limestone. The alkalinity of the water is also evident from the high values of bicarbonate ion present in the water ( mg/l). This was found to be significantly higher than the prescribed WHO values. The slight acidity could result from the presence of the high values of sulfate and nitrate ions in certain locations. In case of upstream samples of the river (RG1 RG5), the turbidity values were found within the permissible limit (5 NTU), while in case of downstream samples of the river (RG6-RG16), all the samples show turbidity values higher than the permissible limit. A possible explanation could be provided with respect to the number of tributaries joining the river. From RG1-RG5, only three smaller tributaries of river Ramganga join it, whereas seven of its major tributaries carrying a higher sediment load join it after the location of RG5. Another reason for the variation in turbidity could be the higher pollution rates in the downstream sampling points of the river. Electrical conductivity was found to be in the range of µs/cm. Values were found mostly to adhere to the 500 µs/cm limits as there has been relatively little anthropogenic activity in the relatively upstream regions of the river. The total hardness of water was found to be in the range of mg/l. All the values of total hardness were found to be below the permissible limit of 300 mg/l. The permanent hardness is also below the permissible limit of 60 mg/l.

4 Table 1: Statistical summary of physiochemical parameters of Ramganga River water quality along with the standard water quality recommended by WHO, 1993 & Bureau of Indian Standards (BIS), 2012 Variable Minimum Maximum Mean Std. deviation WHO, 1993 (Recommended) Temperature( C) ph Turbidity (NTU) EC (µs/cm) TDS (mg/l) F - (mg/l) Cl - (mg/l) NO 3 (mg/l) PO 4 (mg/l) NA - SO 4 (mg/l) Na (mg/l) K (mg/l) Ca (mg/l) Mg (mg/l) HCO 3 (mg/l) Zn (mg/l) * Fe (mg/l) * Pb (mg/l) * Cd (mg/l) * Mn (mg/l) * Sodium was found to be in the range of mg/l and potassium was in the range of mg/l, which are well below the recommended WHO limit of 200 mg/l. It could indicate the absence of sodium and potassium rich rocks. There is a gradual increase in potassium as we go downstream, which could be due to agricultural runoff. The presence of Chloride in the river water varies from to mg/l, which is also well below the limit prescribed by WHO standards. The presence of chloride ion is an indication of hardness of water (Maniappa and Naik, 2007). Upstream values of Chloride are relatively lower than downstream ones, probably because of less anthropogenic activity. The concentration of Sulfate ranged from to mg/l, which is also below the WHO permissible limit of 200 mg/l. The presence of sulfate could be due to use of fertilizers in agriculture, runoff from industries like pulp and sugarcane mills and other anthropogenic activities like the use of soap and detergent. Fluorite was found to be in the range of mg/l, which was under the prescribed WHO limit of 1.5 mg/l. The nitrate ion concentration ranged from to mg/l, which is below the prescribed WHO limit of 45 mg/l.

5 Water types Figure 2: Chemical facies identified on Piper s diagram in groundwater samples In the Piper diagram shown in Fig 2, we look at the relative abundance of the cations and anions. In the cation facies, 50% of the samples fall in the Ca dominant zone, whereas the rest show no dominant type. In the anionic facies, all the samples fall under the bicarbonate dominant zone. In the diamond projection, all the samples fall under the Ca-Mg-HCO 3 - facies. Correlation matrix On observing the temporal variation in total dissolved solids (TDS) and electrical conductivity (EC), it is observed that there is a gradual increase in both parameters as we go downstream. Figure 3 shows that the EC changes roughly by the same proportion as TDS does and is generally just over 1.5 times that of TDS.

6 Figure 3: Correlation between TDS and EC In this study, we used the Pearson correlation coefficient to analyze the temporal variations in the water quality parameters of the Ramganga River and created a correlation matrix. Each value in the matrix refers to the variability of a parameter with respect to another parameter. Nitrate shows strong positive correlation with chloride, fluoride and sulfate. Potassium is seen to have a strong correlation with chloride and nitrate. This could arise due to the use of common Nitrogen and Potassium fertilizers. The moderate correlation of bicarbonate with sodium might arise from anthropogenic sources like sewage and domestic waste discharges. The high correlation of the bicarbonate ion with other ions shows that weathering of carbonate rocks is a major factor determining water quality. Table 1: Matrix of Correlation.

7 Principal Analysis Compound (PCA) PCA is a technique that is used to identify the most significant parameters. On analyzing the current water quality data using PCA, we try to find the dominant factors that determine the water quality by extracting significant Principal Components (PCs). On varimax rotation, it helps us identify the parameters that influence them. There were four PCs with eigen values > 1, which accounts for about 90.60% of the total variance of the entire data set. The first PC accounting for % of the total variance has high correlation with fluoride, chloride, nitrate, sulfate, sodium, potassium, calcium and magnesium. The second PC which accounts for % of the total variance is highly correlated with the bicarbonate and manganese ions. The third PC which accounts of 9.675% of the total variance is highly correlated to Fe. The fourth PC accounts for 6.825% variance do not correlate with any of the variables used in the data. Therefore, most of the data is explained by the first three PCs. Figure 4: Scree plot of eigen values and their cumulative variability Figure 5: Circle of correlation of different variables in F1 and F2.

8 Therefore, the two most significant components are the first two PCs, F1 and F2, which are formed by the planes of the factorial axes. The nature of these axes is revealed by the correlation between the variables and the axes. The scree plot of eigen values and the PCs are shown in figure 4. Figure 5 shows that F1, accounting for % of the total variance is highly correlated with fluoride, chloride, nitrate, sulfate, sodium, potassium, calcium and magnesium, as discussed above. F1 also shows a strong negative correlation with Cd. F2 accounts for % of the total variance. It shows a correlation with the bicarbonate and manganese ions. Conclusion The study takes into account the general water quality and geochemistry of the Ramganga river. The average values of anions followed the trend, HCO 3 - > SO 4 - > Cl - > NO 3 - > PO 4 - > F -, whereas that of the cations was Ca 2 + > Na + > Mg 2 + > K + > Fe. The physico-chemical parameters considered in this study for most samples fell within the permissible limits specified by the WHO and BIS, except for the turbidity, Ca, HCO 3 - and Fe. Although the parameters affecting the water quality are controlled mainly by the weathering of lesser and sub Himalayan rocks, human activities like industrial and agricultural run-off affects the water quality adversely, making it unfit for drinking. Therefore, a check must be put on these activities by municipal or urban and rural local bodies to preserve the water quality.

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