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Results and Discussion
Stream water is being used for domestic purposes, irrigation, recreation, etc. Mapping and monitoring of water quality would help in maintaining the quality and sustainable management of the ecosystem. Water sampling was done at stations depending on the water availability in streams. Some streams are perennial like YK, YNK, BGT, BE1 and AGT2. AG1 and HA1 dries up in post monsoon season whereas, AG1, AGT1, MH1 and HA1 dries up during pre-monsoon. Variability in the physico-chemical parameters of streams monsoon, pre-monsoon and post-monsoon seasons are presented in Figure 2. Tables 2a and 2b lists water quality across sampling locations for monsoon and post-monsoon seasons respectively.
All ion values were very high in all seasons at Yaana in comparison to other streams due to anthropogenic stress. Yaana is a popular eco-tourist place visited by large number of pilgrims every day, and due to mismanagement of solid and liquid waste the stream is polluted. Turbidity ranges from 1.1 – 51.45 NTU and is very high in monsoon due to silt transport during runoff. pH which measures the alkalinity and acidity of water and influences chemical reactions in water bodies. pH in the sampled streams ranges from 6.7 – 8.6 and values are higher in post-monsoon and low during monsoon due to the presence of organic matter.
Dissolved oxygen in streams fluctuates due to movement/mixing of water, organic pollutants, photosynthetic and respiratory activities by flora and fauna in aquatic ecosystems. DO ranges from 5.45 – 16.26 mg/L and higher values during monsoon due to rapid water discharge with the aeration of water. COD ranges from 50.6 -17.71 mg/l and BOD ranges from 33.33 – 6.98 mg/l and higher BOD and COD values reflect the presence of organic matter. For unpolluted to moderately polluted water, BOD5 values ranges between >1.0 to <10.0 mg/l (Salman et al. 2013). Turbidity, orthophosphate, BOD and COD were very high in monsoon due to inflow of suspended matter and organic compounds into streams with the catchment run off. TDS and EC are very high in pre-monsoon season, but very low in monsoon. TDS ranges from 104.67 – 19.9 mg/l whereas EC ranges from 194.33 – 39.4 µS. Variations in electrical conductivity are brought about by the inorganic dissolved solids such as chloride, calcium, magnesium, aluminium, nitrate, sulphate, sodium and iron. Organic compounds such as oil, phenol, alcohol and sugar are bad conductors and thus, affect the electrical conductivity (Gandaseca et al. 2011; Al-Badaii et al. 2013). The water discharge is very high at HA1 during monsoon (358.4 mm/day). In pre-monsoon season, water temperature, total alkalinity, chloride, total hardness, calcium and magnesium were very high because of very less water level and high evaporation rate. But, ion contents like chloride, total hardness, calcium and magnesium and nitrate were very low in monsoon season because of dilution effect.
Turbidity and ortho-phosphate were present in all sampling stations due to the entry of enormous quantity of rain water from the catchment during monsoon (Table 2a). The ion contents (TDS, EC, chloride, total hardness, calcium, magnesium and sodium), pH, total alkalinity were less due to the dilution with precipitation. Similar study reports of increased suspended solids, turbidity and COD during monsoon as the rivers received silt and debris from the catchments, which lowered the ionic contents due to the dilution (Rani et al. 2011). Large amount of phosphates entered the stream in rainy season from surrounding catchment areas dominated by rocks (Singh et al. 2013).
During post-monsoon season (Table 2b), high pH and DO prevailed due to increased algal photosynthesis. The turbidity had decreased due to low discharge while organic matter and nutrient levels (COD, ortho-phosphate, nitrate, potassium and BOD) decreased due to enhanced algal uptake and microbial activity. The water temperature in post-monsoon appeared to be suitable for the phytoplankton growth and reproduction (Nassar et al. 2014). Higher chloride levels in post-monsoon season was due to reduction in water levels and concentration of salts with the enhanced evaporative losses at higher temperatures (Shetty et al. 2013). The DO level depended on all the abiotic and biotic factors (Hacioglu and Dulger 2009) evident from higher DO levels with turbulence and lowered DO during higher organic content with escalated decomposition rates. Similarly, DO vary with temperature (Arslan 2009).
The sampling sites had high ionic (TDS, EC, total hardness, calcium, magnesium, sodium) and organic content (COD and BOD) but low DO and water discharge during pre-monsoon period (Table 2b). Chandrabhaga River, Maharashtra had maximum BOD of 31mg/l in summer and minimum BOD recorded was 9.9 mg/l in winter (Watkar and Barbate 2015). During pre-monsoon season, YK was found to have high pH and ion contents such as TDS, EC, total alkalinity, total hardness, calcium and magnesium. Turbidity, orthophosphate, sodium, water discharge and DO were higher in YNK. COD, water temperature and chloride were higher in BGT. Temperature and precipitation influences the discharge pattern in rivers (Kriauciuniene et al. 2012). Variations in temperature alter the physico-chemical properties of water and accelerate various chemical reactions as well as metabolic activities. BOD and nitrate are higher in BE1. The amount of nitrates in water increases due to heavy rainfall, land drainage, oxidation of ammonia (Vankar et al. 2018); and the agricultural activities which makes use of huge amount of chemical fertilizers and animal farming (Dunca 2018).
Fig. 2. Variations in water quality among 9 select streams in monsoon, post-monsoon and pre-monsoon season
Principal Component Analysis (PCA)
In order to prioritize the factors affecting water quality of the sampled streams, PCA was performed on data for monsoon, pre-monsoon and post-monsoon seasons. PCA of 18 physico-chemical variables pertaining to water samples from 9 different sampling points (during April, 2014 to March, 2016) helped in understanding the main decisive factors of stream water quality across seasons. PCs chosen based on Eigen values (of 1.0 or greater are considered significant), which explained maximum variance of experimental dataset (Fig. 3) and are grouped as “strong” (>0.75), “moderate” (0.75 - 0.50) and “weak” (0.50 - 0.30), according to the loading values (Liu et al. 2003).
Here, the first PC corresponds to the higher eigenvalue (10.76), accounting for 59.79 percent of the variance with strong positive loading (>0.75) on pH, calcium, magnesium, ortho-phosphate, nitrate, potassium, DO and discharge, whereas high negative loadings on WT, EC and total alkalinity during monsoon (Fig. 3a). PC 2 corresponding to the second eigenvalue (4.12) accounted for 22.87 percent, contributed by BOD. PC 2 showed moderate positive loading (>0.50) on Water temperature, COD, chloride, BOD and sodium. The third factor corresponding to the third eigenvalue (1.68) accounted for about 9.32 percent showed high positive loadings on turbidity.
During post-monsoon (Fig. 3b), PC 1 explained seventy-five percent of the total variance (eigenvalue of 13.50) and showed strong positive loading (>0.75) on TDS, EC, total hardness, calcium, magnesium, ortho-phosphate, nitrate, potassium and water discharge, whereas high negative loadings on water temperature, pH, COD, total alkalinity, chloride and DO. PC 1 showed moderate positive loadings (>0.50) on sodium, BOD and DO. PC 2 corresponding to the second eigenvalue (1.66) accounted for 9.21 percent of the total variance, showed moderate negative loading on turbidity. PC 3 (eigenvalue of 1.39) accounted for 7.73 percent of the total variance showed moderate positive loading (>0.50) on sodium.
During pre-monsoon (Fig. 3c), the first PC explained 63.45 percent of the total variance (eigenvalue of 11.42) and was best represented by turbidity, total hardness, calcium, magnesium, ortho-phosphate, nitrate, potassium and discharge. PC 1 showed strong negative loadings on WT, COD, chloride and BOD and moderate positive loading on DO. PC 2 corresponding to the second eigenvalue (4.47) accounted for 24.83 percent of the total variance was loaded by TDS, EC and pH. The third factor corresponding to the second eigenvalue (1.47) accounted for approximately 8.17 percent of the total variance showed moderate positive loading on sodium and turbidity.
Thus, PCA revealed, the parameters like EC, TDS, ortho-phosphate, nitrate, total hardness, calcium, magnesium, potassium and water discharge played an important role in these sampling sites. These variations are due to varied land uses in the catchments of lotic ecosystems – Yaana (YK), and Nanalli (YNK) has evergreen forest whereas Beilangi (BE) has mixed type of forest. The other sampling sites like Harita (HA), Mastihalla (MH), Aanegundi (AG), Aanegundi tributary 1 (AGT1), Aanegundi tributary 2 (AGT2) and Bialgadde (BGT) have mixed land use dominated by horticulture and agriculture activities. Landscape alterations in catchment due to the anthropogenic factors changes the quantity (stream flow) and quality of streams (Petersen et al. 2017). Water discharge played an important role in the present study. The marked difference in seasonal variations in river discharge and concentration of pollutants is due to variations in precipitation, surface run-off, interflow, groundwater flow etc. (Singh et al. 2004).
Cluster Analysis
Cluster analysis of physico-chemical parameters of different streams in Aghanashini river basin showed varied patterns during monsoon, post-monsoon and pre-monsoon seasons (Fig. 4). Four clusters were evident based on water quality parameters of monsoon (Fig. 4a). Harita has high water temperature, turbidity, COD, orthophosphate, nitrate, sodium, potassium, BOD and water discharge. AGT2, YK and Mastihalla had high ionic contents as evident in levels of TDS, EC, total alkalinity, total hardness, calcium and magnesium. BGT, AGT1 and YNK had high total hardness, DO and alkaline pH. Beilangi and AG had high chloride but comparatively low pH, turbidity, calcium, total hardness, nitrate, DO and water discharge. Among all the stations, Harita had highest discharge in monsoon season which had influenced the water quality.
Figure 4b illustrates of the three clusters during post-monsoon. YK reveals of disturbance with high TDS, pH, EC, COD, total alkalinity, total hardness, magnesium, ortho-phosphate, nitrate, DO and water discharge but low water temperature, chloride, sodium and potassium. BE, AGT1 and Mastihalla had high water temperature but low water discharge, ionic, organic and nutrient levels. YNK, AGT2 and BGT had high turbidity, chloride, sodium, potassium and BOD. During pre-monsoon, about four clusters are evident in Figure 4c. BE had high nitrate and BOD but low ionic contents, ortho-phosphate and discharge. BGT had high water temperature, COD and chloride. YNK and AGT2 had high turbidity, ortho-phosphate, sodium and potassium. YK had high TDS, EC total alkalinity, pH, DO, total hardness, magnesium and calcium. Yaana is famous for two rocky outgrowth of solid black, crystalline karst limestone. This is evident from the sampled water at Yaana with high ion contents and pH due to the influence of calcium carbonate. All stations showed wide seasonal variations in all the physico-chemical parameters mainly due to variations in discharge. Climate, watershed characteristics and forest cover also play a decisive role in quality and quantity of water in a forested watershed (Gokbulak et al. 2017).
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