Study area
The important river Damodar (563 km) originates from Khamarpat hill under Palamau district of Jharkhand state (India). It flows toward east direction and ultimately it joins with river Bhagirathi-Hooghly in West Bengal. Upper and middle parts of the river basin have rich diversity of minerals and standard quality coal reserve of Gondwana formations. Abundant supply of fresh river water with high mineral and energy resources attracts many large, medium and small-scale industries since historical time. River Damodar is the principal supplier of water resource to drinking, industrial and domestic purpose in its catchment area. Therefore, such favourable environment attracts huge population along with industrial integration in this area. The present study area is bounded by 23° 28′ 28.7″ N to 23° 40′ 52.5″ N and 86° 49′ 26.8″ E to 87° 18′ 42.4″ E and 65.37 km river stretch has been selected for the study. In this section high, agglomeration of industries and allied human works intensively developed along the riverside. Many iron and steel plants, thermal power plant, sponge iron factory, chemical industries, coal mining fields and urban centres have been developed through the evolution of time. As a result, huge untreated waste (solid/ liquid), hot water, coal dust and urban effluents are being regularly discharged to the riverbed through various connecting channels which are locally called nallas (Fig. 1)10,11.
source QGIS 3.16 software (https://qgis.org/en/site/forusers/download.html).
Location map of the study stretch of a tropical river Damodar (India). The diagram is prepared by open
Sample collection and data analysis
Water samples were collected from eleven discharged points of industrial effluents on main riverbed. First, samples were taken on December 2019 (pre-lockdown/ normal period), again second, samples were collected in June, 2020 (during lockdown) to assess the changes on river water quality due to temporarily closing of industries. Third, samples were obtained in November, 2020 (after unlock phase) to get clear idea about effects of industries on the river water quality. Samples were obtained from 0.5 m below the surface water level within 5 m influencing radius zone. Pre cleaned polyethylene bottles (500 ml) were used for the collection of five subsamples from each sampling site and mixed up to get a bulk contain (1 l). All samples were carried properly for further analysis in laboratory. Sample containers were labelled as S1, S2, S3… to S11 for properly identification (Fig. 1). Total 20 parameters were analysed from each sample of each period. Important parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS), turbidity, magnesium (Mg2+), calcium (Ca2+), chloride (Cl–), sulphate (SO42–), nitrates (NO3−), Biological Oxygen Demand (BOD), Dissolved Oxygen (DO), zinc (Zn2+), cadmium (Cd2+), lead (Pb2+), nickel (Ni2+), chromium (Cr), iron (Fe2+), chlorophyll a (Chla), total phosphorus (TP), and Secchi disk depth (Sd) have been considered. Consequently, pH and EC were measured at the sampling sites using Thermo probe, Hanna HI9811-5 potable meters respectively. DO was determined through Winkler’s method at the sampling spot immediately28. EC denoted by microsiemens per centimetre. TDS was determined following the procedure given by Hem (1991). Turbidity was denoted by Nephelometric Turbidity Unit (NTU’s). All cation, anions, BOD and DO were expressed in mg/l while all heavy metals, TP and Chla denoted as microgram/l. All other physico-chemical parameters and heavy metals were analysed by standard procedure which was prescribed by American Public Health Association (APHA)29. Chla and total phosphorus were estimated following APHA29 standard procedures. Secchi disk (Sd) with 8 in. diameter and attached cord in disk centre was used for depth measurement and expressed in meters at the maximum limit of depth where disk was seen from the above into the water.
Modified water quality index (MWQI)
MWQI of the 33-sample water was conducted for 11 sample sites by important water quality parameters namely pH, TDS, EC, turbidity, Mg2+, Ca2+, Cl–, SO42–, NO3–, BOD and DO. We considered 11 variables per sample in the index. The calculation of MWQI was conducted following the method of Vasistha and Ganguly30.
At first, pre defined weightage was assigned for each selected parameter. The weightage of each parameter was obtained from previous literatures. After that, relative weight of each parameter was derived by the formula.
$$ RW = AW/sumlimits_{i = 1}^{n} {AW} $$
(1)
where RW is relative weight of each parameter, AW is assigned weight obtained from past literature (AW of pH = 1, TDS = 1.79, EC = 1.78, turbidity = 1.09, Ca2+ = 0.8, Mg2+ = 0.72, Cl– = 1.28, SO42– = 1.60, NO3– = 2.32, BOD = 1.72, DO = 2.85) and n is total number of parameters considered for analysis.
Second, quality assessment (Qi) of each parameter was obtained following the formula.
$$ Q_{i} = (C_{i} times S_{i} ) times 100 $$
(2)
where Ci is concentration of particular parameter in sample water, Si is standard permissible limit of each parameter as suggested by BIS31 and WHO31 (Table 1).
Qi for pH and DO was obtained through some modification of Eq. (1.2) because optimum concentration of these two parameters are little different from others. The optimum value of pH and DO is considered as 7.0 and 14.6 mg/l (100% saturation at 23 °C), respectively32. Thus, Qi for these two parameters were performed using the formula.
$$ Q_{i} = (frac{{C_{i} – V_{i} }}{{S_{i} – V_{i} }}) times 100 $$
(3)
where Vi denotes optimum values of pH and DO.
Third, in this step sub index (SIi) was calculated for each considered parameter by multiplication of relative weight (RW) with quality assessment (Qi) value of each parameter using formula below.
$$ SI_{i} = RW times Q_{i} $$
(4)
At last, MWQI was obtained for each sample site by summation of SIi of each parameter as below:
$$ MWQI = sumlimits_{i = 1}^{n} {SI_{i} } $$
(5)
Water quality (based on MWQI values) has been categorised into 5 classes such as excellent (≤ 50), good (50–100), poor (100–200), very poor (200–300) and unfit for drinking (≥ 300) as suggested by BIS31 (IS:10500).
Heavy metal index (HMI)
Analysis of heavy metal index was done using 6 parameters as Cd2+, Zn2+, Cr, Pb2+, Ni2+, and Fe2+. Calculation was conducted through this formula33.
$$ Wi = K/Si $$
(6)
where Wi suggests weightage of ith parameter, K means constant value (1), Si means standard value of ith parameter as per BIS31, and WHO32. In the next step, sub index calculation (Qi) was done through this formula.
$$ Qi = sumlimits_{i = 1}^{n} {frac{Mi}{{Si}}} times 100 $$
(7)
where Mi is the value of heavy metal concentration in sample water, Si is maximum limit of permissible of ith parameter in µg/l according to BIS31 and WHO32 (Table 1). At last, HPI was calculated using this formula which is given below.
$$ HPI = frac{{sumlimits_{i = 1}^{n} {WiQi} }}{{sumlimits_{i = 1}^{n} {Wi} }} $$
(8)
where n indicates total number of parameters used for calculation of HPI. HPI can be classified into five categories such as excellent (0–25), good (26–50), poor (51–75), very poor (75–100) and unfit for drinking (> 100).
Potential ecological risk (RI)
To assess the environmental response of heavy metal contamination, a new index was applied from sedimentological perspective and it was proposed by Hakanson33. In this method, effects of heavy metals on environment and possibilities to ecological risk can be determined by a single contamination coefficient, toxic response coefficient of heavy metals and comprehensive contamination of metals for any aquatic or soil environment using this formula34.
$$ C_{f}^{i} = C_{s}^{i} /C_{n}^{i} ,;c = sumlimits_{i = 1}^{n} {C_{f}^{i} } $$
(9)
$$ E_{r}^{i} = T_{r}^{i} times C_{f}^{i} ,;RI = sumlimits_{i = 1}^{m} {E_{r}^{i} } $$
(10)
where Csi specifies heavy metal contamination value, Cni indicates reference value of heavy metals, C stands for degree of contamination by toxic heavy metals, Eri represents ecological risk factor of any single substance, Tri indicates ‘Toxic- response’ of any particular metal and RI denotes potential ecological risk index of all measured toxic metals. In this study, reference value of heavy metals was taken from standard preindustrial values of heavy metals as Cd = 1.0, Pb = 70, Cr = 90 and Zn = 175. Toxic response of heavy metals was used as follows: Cd = 30, Pb = 5, Cr = 2 and Zn = 1 (Hakanson33). Values of RI can be classified into four categories such as Practically uncontaminated (< 150), Moderately contaminated (150–300), Heavily contaminated (300–600), and Extremely contaminated (> 600).
Trophic State Index (TSI)
Trophic status of river was identified by Trophic State Index (TSI) considering three parameters such as Secchi disk depth (Sd), Chlorophyll-a (Chla), Total phosphorus (TP). Trophic State Index (TSI) was calculated by Carlson method35.
$$ TS(Sd) = 60.0 – 14.41 times Ln(Sd) $$
(11)
$$ TS(TP) = 14.42 times Ln(TP) + 4.15 $$
(12)
$$ TS(Chla) = 30.6 + 9.81 times Ln(Chla) $$
(13)
$$ {text{TSI }}left( {text{Trophic State Index}} right) = left[ {TS(Sd) + TS(TP) + TS(Chla)} right]/3 $$
(14)
Values of TSI were classified into seven categories such as low oligotrophic (< 30), high oligotrophic (30–40), mesotrophic (40–50), (Mesotrophic), low eutrophic (50–60), medium eutrophic (60–70), high eutrophic (70–80), and very high eutrophic (> 80).
Statistical and spatial analysis
A meta analysis such as descriptive statistics, Pearson correlation coefficient, analysis of variance (ANOVA test), principal component analysis (PCA) of all physico-chemical parameters, biological and heavy metals were applied to quantify the significant changes in three phases using least significant difference (LSD) at 0.05 level. All statistical analysis has been performed using SPSS 20 and MS-excel software while R programming language v. R 4.1.1 is used only for diagrammatic presentation. Inverse Distance Weightage (IDW) technique was performed on QGIS v.3.16 software for revealing spatial variation of water quality in three periods on the basis of different indexing method.
Source: Ecology - nature.com
