Assessment of Water Quality with Special Reference to Hydrochemistry: A Case Study of Auranga Estuary, Valsad, Gujarat, India

Abstract

An assessment of Water Quality from Auranga estuary (20°63’ N and 72°820 E) was carried out from January 2019 to December 2019. The hydro-chemical variables were analyzed for the evaluation of water quality showed fluctuation in the estuarine water seasonally. The water quality index was computed for the evaluation of water quality of Auranga estuary; to know the pollution level of water body Index for Pollution was also computed. The water quality index (WQI) was 115.97 at downstream and 85.30 at upstream that indicate poor and good water quality respectively. The Pollution Index (PI) ranges from 1.41 (Downstream) to 0.78 (Upstream) which indicate that the water is medium polluted and slightly polluted respectively. Seasonal assessment showed the discrete water quality index and pollution index based on three different seasons; during winter season WQI was 143.30 and 108.05 and PI was 1.41 and 0.97 at downstream and upstream respectively, during summer WQI was 126.73 and 106.95 and PI was 1.18 and 0.94 at downstream and upstream sites respectively and during monsoon WQI was 97.67 and 88.11 and PI was 0.88 and 0.78 at downstream and upstream sites respectively. Univariate statistical technique is attempted to explain the correlations between the variables.

1. Introduction

Marine and freshwater both ecosystems are incorporated to the estuarine ecosystem and make it a functional water body [1]. The productivity and sustainability of coastal, marine and estuarine ecosystem largely depends on the coastal water quality [2]. Estuaries support important biogeochemical processes that are central to the planet’s functioning, e.g. nutrient cycling. As estuaries concentrate waters from very large land surfaces into relatively small water bodies; the biogeochemical processes and trophic interactions within estuaries can play an important role in the management of water quality problems [3]. The surrounding civilization of mankind and their productivity are significantly affected by the water quality. Although, in the developing countries the rivers have faced consequential problems due to the rigorous anthropogenic activities along the water bodies [4]. The seagoing rivers received pollutant components from the transition zone of sea water and fresh water as well as marine pollutants due to the sea water intrusion. There should be more consciousness paid to the spatio-temporal assessment of water quality because of their extensive economic expense and several ecological roles. The most effective and common practice for evaluation of environmental problems is long-term assessment of water quality since the spatio-temopral fluctuations of hydrochemical parameters and biological variables can be conferred clearly and can help in future for research on evaluation of polluation status [4]. The hydr-chemical status of estuaries varies both temporally and spatially and the quality of water is usually described based on its physical, chemical and biological factors and in accordance to the distance from the coastline area as well as tidal phase various responses showed by the water quality of water bodies. The dissolved elemental loadings in the estuaries vary spatially (based on distance from mouth) and temporally (diurnal, seasonal and inter-annum) as well as with depth and laterally, hence the estuary is more fluctuated than sea waters.

The water quality index (WQI) is a spatial trend for determining the depletion of water quality because of the locus of crucial pollutant resources. Water quality evaluation is required for the investigation of water quality, water pollution and their acquaintance of main pollution effective causes, as well as the recognization of polluted risky regions through that polluted surrounding water bodies as well as scrutiny of the diversity of living components [5]. From diverse kinds of pollutions, aquatic environmental pollution has a vital threat to mankind health, also becomes the most remarkable issue for the sustainable development [6]. To determine the water quality of estuaries several factors perform significant role including the quanity and quality of fresh water as well as marine water, biological systems and water circulation and movement. The alternations in these systems can be natural or affected by civilization and artificial activities as well as their catchments [7]. Varol et al. pointed out in 2012 that in times ahead the freshwater is becoming a scanty source with monitoring of water quality and it is a very serious matter in the current decades [8]. The estuarine environment is a very vital for the procreation and natural susceptibility to diequipoise of environment of many marine organisms; that’s why there is a need for special attention to estuaries [9]. The rainy and post-rainy seasons significantly influence the freshwater inflow to the estuarine area. The hydrochemical qualities of water body varied according to varying freshwater flow and such variations depend on several ecological reactions like fluctuations in composition of species, growth of phytoplankton blooms and reduction of oxygen concentrations. The fluctuation in water quality is a continuous process [10]. Tropical estuaries have more pronounced nutrient dynamics as well as tidal variation in comparison to temperate estuaries [11]. For sustainable utilization and conservation of water resources it is necessassery to identify the water pollutants and spatio-temporal assessment of water quality [10]. The water temperature and discharge found affiliated to the climatic constituents include hydrochemical and biological systems as well as flow regulation that is closely linked to the seasonal variation of water quality [12].

The rapid growth of urban areas and industries has an excess demand of water and that is why limited water resources are under tremendous pressure. An urban land scenery established due to the higher developed industrialization in India and it gives rise to problems on water pollution dangerous to all living beings. The water resources are getting polluted due to the untreated effluent discharges and industrial dumping off in to the water pits and water channels [13]. Mankind activities such as garbage dumpings, utilization of agricultural fertilizers and chemicals with its rapid utilization of water resources affect the water quality [6]. A large number of components and corresponding evaluation factors are necessary for the assessment of water quality at the basin scale, as well as a geographical distribution of pollution levels based on every component and evaluation factor. Understanding the temporal trends and spatial distributions of water quality are essential for maintaining the health of aquatic ecosystems and ensuring the safety of water [14]. Decline in water quality is mainly due to the increased concentration of various pollutants such as oils, heavy metals, nutrients and organic compounds [15]. Deterioration of water quality also occurred through the efflux of suspended solids, such as erosion from river banks, sediment and silt, agricultural discharges, wash-off from logging fields and construction sites, which are affecting the various bodies of water, thereby aquaculture respiration becomes impaired, primary productivity and depth of water bodies become reduced, and aquatic ecosystem become suffocated.

There are a large amount of complicated phenomenon and multiple-factor in comprehensive water quality estimation, and many more fuzzy concepts and phenomena are entailed in an evaluation. The water quality index (WQI) is a numeric expression which is used for the water quality assessment of a selected water body; thereby it is possible to easily understand the condition of a water body by managers from many countries [16]. At first Horton evolved WQI in 1965 in the United states by choosing the 10 most commonly used factors for the assessment of water quality such as Chloride loadings, Alkalinity amount, pH and Dissolved oxygen concentration, etc. and it has been broadly used and undertaken in Asian, European and African countries [17].

Nowadays, the literature on water quality from inland rivers and coastaline areas can be obtained easily, however there are very few reports on information of sea Voyage Rivers because of their complex ecosystem and diverse pollution resources. Literature on some of the spatio-temporal assessment of estuarine ecosystems includes Motru river estuary, Romania [16]; Estuarine systems from South Africa [7]; Estuary of Duliujian river, China [4]; Scheldt estuary, Belgium and Netherlands [3]; Zhangweinan river basin, china [10]; Ying river basin, china [12]; Tapi etsury, west coast of India [11]; Narmada estuary, Gujarat, India [18]; Bay of Bengal, India [19].

One of the fundamental steps in establishing such an integrated water management approach is the development of an integrated monitoring programme. This study explicitly considers the spatio-temporal dependence model for overcoming spatio-temporal variability. The relationship of water quality parameters observations vary with time and space. The water quality of the Auranga estuary from western India was assessed according to spatial and temporal fluctuations and was the main aim of this case study. A WQI considers the spatio-temporal coefficient can sufficiently explain the spatial and temporal variations in the quality of water from a target area. This research aims to reveal the water quality status based on WQI. The objective of this study is to find out the main pollutants in different seasons and estuarine reaches by multivariate statistical methods, which are expected to help managers to understand the water body system along the estuary.

2. Materials and methods

2.1 Study area

Western Indian state Gujarat has 33 districts and Valsad district is one of them. There is the longest coastline about 1600 km of India occupied by Gujarat; of that 73 km of coastline is occupied by the Valsad district (Figure 1(a)). Auranga river originates from near Bhervi village and flows through Valsad taluka as well as city and ends into the Arabian Sea (Figure 1(b)). It flows across Kosamba, Bhadeli, Lilapore, Vejalpore, Gundlav, Abrama, Jujwa, Ghadoi, Kalwada, Nandhai, and Bhervi villages. The Auranga river has 97 km in length with 699 sq./km catchment area. AN estuary of Auranga is located under 20°63’ N Latitude and 72°82′ E Longitude. Tithla beach is located near the Auranga estuary. This river is very important for the socio-economic life in the southern Gujarat.

Figure 1.

(1a) – Geographical locations of Gujarat in India and Valsad District in Gujarat; (1b) – Estuarine area and sampling sites from Auranga estuary.

The water resource of Auranga hydrographical complex is providing the drinking water supply as well as the exploitation of water for industrialization as well for domestic purposes, which can influence the hydro-morphological characteristics of tributary, changing the conditions of the liberated natural water regime on their courses.

2.2 Sample collection

The sampling activity was conducted from four sites (Figure 1(b)) of the solely flowing Auranga estuary based on bi-monthly intervals from January to December 2019 which include all three seasons; winter, summer, and monsoon. A total of 24 samples were analyzed that includes physicochemical parameters including heavy metals. Three samples were collected from each sampling site and then made into composite samples. The sampling sites were selected based on resources available for sampling, experimental sampling, and checked water quality parameters. The water samples were collected by using 1-liter clean polythene bottles and stored in an ice box at 4° C temperature and then transported to the laboratory as soon as possible for physicochemical parameters analysis. The estuarine water samples were fixed in 300 ml BOD bottles for the immediate estimation of dissolved oxygen and measurement of biochemical oxygen demand after 5 days of incubation at 20° C in an incubator.

2.3 Water quality assessment

Hydro-chemical parameters were analyzed in 7 to 10 days immediately after the water samples were collected, the analysis methodology strictly follows the protocols described in manuals [20, 21]. Water temperature was determined by Thermometer, Electrical Conductivity was determined through the digital conductivity meter and pH was measured by digital pH meter on-site during sampling. DO was analyzed on-site and BOD was analyzed after 5 days incubation period through the Winkler method. Other physicochemical parameters analysis was carried out in the NVPAS laboratory. Turbidity was determined with the Turbidity meter. Alkalinity, Salinity, Free CO₂, Chloride, Total Hardness, and Ca Hardness were analyzed through the titration method. COD, Ammonium, and Color were analyzed in SICART. Nitrate, Inorganic Phosphate, and Silicate were determined with the help of the Spectrophotometric method. The gravimetric method was applied for the assessment of TSS, TS, and TDS. A flame photometer was used to assess the Sodium and Potassium concentrations. The Turbidimetric method was implemented for Sulfate assessment. Heavy metals were analyzed through the ICP-OES in SICART.

The Water Quality Index (WQI) is mostly applied for the evaluation of the water quality of a particular water body. The WQI can be divided into five groups, each group with a different quality state and with a different usage domain [22]. Here a mathematical equation incorporates several quantitative variables that give the scale in numbers of the quality of water bodies.

2.4 Computation of WQI

The WQI is computed through the following three steps [23].

First step – Based on the concerned significance for the overall quality of water, assigning of weight (wi) to the selected water quality variables (e.g., Chloride, pH, Temperature, TDS, Phosphate, Nitrate, Iron, Boron…) (weight may be from 1 to 5).

Second step – Compute the relative weight (Wi) of the selected variables by using the following equation:

$$\mathit{Wi}=\frac{\mathit{wi}}{\sum \mathit{wi}}$$E1

(i = 1 to n; n = total number of selected variables)

Wi = Relative weight,

Wi = Assigning weight of each variable and ‘n’ is the number of variables.

Third step – Find out the quality rate (qi) for each selected variable, as below:

$$\mathit{Qi}=\left(\frac{\mathit{Ci}}{\mathit{Si}}\right)\times 100$$E2

Qi = Quality rating scale,

Ci = Concentration of each selected variables.

Si = Guideline value/desirable limit as given in Water Quality Standards (Table 1).

Sr. No.	Parameters	Units	Prescribed standards
1	Chloride	mg/L	250.0***
2	Boron	mg/L	0.7****
3	Phosphate	mg/L	0.001–0.01**
4	Sulfate	mg/L	250***
5	DO	mg/L	4.0*
6	pH		6.5–8.5*
7	Temperature	°C	26–30**
8	Nitrate	mg/L	50***
9	TDS	mg/L	1000***
10	Color	Hazen	150**
11	Alkalinity	mg/L	115*****
12	COD	mg/L	20***
13	Iron	mg/L	0.3***

Table 1.

Water quality standards for coastal waters.

* Water Quality Standards for Coastal Waters Marine Outfalls. SW-II Standard. Central Pollution Control Board, New Delhi.; ** South African Water Quality Guidelines for Coastal Marine Waters, 1996. International Target Values for the Natural Marine Environment, Vol.1, pp. B-1-B-3. and Chap. 4.2. pp. 31.; *** KepMenKes No. 51/MENKES/SK/VII/2004. quality standards of the Environment Decree No. 51 in 2004 on Marine water quality standard for marine biotas.; **** UK Marine Standards.; ***** Canadian Water quality standards for Marine fisheries and aquatic life, Environment Canada, 1987 CEC, 1978, 1980 committee for fisheries, 1993.

Fourth step - For the computation of WQI, the sub-index (SI) is first determined for each chemical variable, as follows:

$$\mathit{SIi}=\mathit{Wi}\times \mathit{Qi}$$E3

$$\mathit{WQI}=\sum _1^n\mathit{SIi}$$E4

SIi = Sub index of i^th variable;

Wi = Relative weight of i^th variable;

qi = Quality rating scale of i^th variable and ‘n’ is the number of selected variables (Table 2).

CWQI- range	Category-rank
<50	Excellent water
50–100	Good water
100–200	Poor water
200–300	Very poor water
> 300	Unsuitable

Table 2.

Coastal water quality ranking criteria [15].

2.5 Calculation of pollution index

Single-factor pollution index was formulated as [24]:

$$\mathrm{Pi}=\mathrm{Ci}/\mathrm{Si}$$

Where, Pi = the pollution index.

Ci = the measured concentration of variables (pollutants).

Si = Guideline value/desirable limit as given in Water Quality Standards (Table 3).

Pollution index (PI)	Pollution category
0.4	Not-polluted
0.4 ∼ 1.0	Slightly polluted
1.0 ∼ 2.0	Medium polluted
2.0∼ 5.0	Highly polluted
>5.0	Serious polluted

Table 3.

Standard values of pollution index.

DOI:10.1371/journal.pone.0119130.t002

All mathematical and statistical computations were made by PAST 3.0.

3. Result and discussion

To protect the environment in general and preserve good water quality in particular, an effective and modern water management system is necessary. For the monitoring of water quality of Auranga estuary the water quality index was computed for the period of a year 2019 from two sampling sites; downstream near Divadandi light house, Kosamba, and upstream near Valsad water treatment plant, Abrama taking into account the maximum annual, the minimum annual, and the mean annual values of 26 following physical and chemical parameters: Color (Hazen), Alkalinity (mg/L), Free Carbon Dioxide (mg/L), Electric Conductivity (μs/cm), Turbidity (NTU), Temperature (°C), pH, Salinity (ppt), Silicate (mg/L), Hardness (mg/L), TDS (mg/L), TSS (mg/L), DO (mg/L), BOD (mg/L), COD (mg/L), Chloride (mg/L), Sulfate (mg/L), Sodium (mg/L), Potassium (mg/L), Nitrogenous compounds such as Ammonium (mg/L) and Nitrate (mg/L), and Phosphate (mg/L) and presented Trace metals (Boron and Iron) (mg/L) with units of measurement adapted according to “International Union of Pure and Applied Chemistry”.

Water quality monitoring is not only the scientific description of status of water body, but also revealed the directions for control and management programs of water pollution. From this water quality monitoring program, the appropriate model about water quality can build through the received information. The models of water quality and parameters identification can be determined through the assessment of water quality. This kind of model accurately revealed the status of water body, master resources of pollution, trends of development, and scientific methods to protect the aquatic ecosystem with planning and proper management [25].

In the case of physical parameters, the annual average values of color and turbidity were higher downstream than upstream site. The turbidity is in a dynamic state and is significantly changed during heavy rainfall events. Several factors are affecting the turbidity such as sunbeam, apparent water state as well as the removal of suspended compounds from the terminal water flow and water column. Apart from causing variations in the surface water quality, rainfall can directly increase the level of suspended solids through runoff. Temperature and pH were almost similar at both sites of Auranga estuary based on the annual average value. The meteorological properties fluctuated the temperature. An alkaline feature of this water body was noticed with pH (Average of 7.4, varied from 6.8 to 7.7) is designating that this water body has limited variations of pH values due to the presence of buffering capacity. Similar observation about pH range 7.2–7.6, with high pH in winter was made from the Timis river basin [26]. The effects of pH on phosphate adsorption should be responsible for strong positive correlations of phosphate. In the alkaline state, the ion exchange released phosphorus thereby; metal cations were replaced by OH− and combined with phosphate consequently leading to more dissolved phosphate contamination [4]. Alkalinity, Chloride, Salinity, and sulfate had high annual average concentrations in downstream than upstream site because of the higher content of seawater than fresh water in the study area. More salinity during the periods of winter and summer was due to the high degree of evaporation of exterior surface water and the adjoining neritic water domination as well as the low-lying wave and tidal activity with reduced freshwater inflow and land drainage. The minimum salinity was during monsoon (Table 4) due to the monsoonal rain, flooding, and freshwater input into the study areas. The existence of large amounts of organic materials leads to excessive contamination of chloride in water. A large amount of chloride in water indicated the pollution of animal origin, hence chloride concentration and pollution status have a direct correlation. The poor contamination of chloride during the rainy season (Table 4) was possible because not many loadings from the industrial activity while, the higher concentration of it may be due to seawater intrusion coupled with a huge influx of sewage and industrial wastewater [3]. The calcium concentration fluctuates with variables such as land field, precipitation, and dissipation in the coastline waters constituting close to the shore. At the early stretches of estuarine transition, excess calcium amount attributed to their exemption from the interchangeable sites of water body’s clays with other cations [3]. The total suspended solids (TSS) increased at the middle of the estuary and further downstream due to the inrush from the upper stretches, wastewater discarding and the usage of traveling boats and fish catching boats for caged fish rearing. The annual average value of electrical conductivity was higher at the downstream site than at the upstream site because of more content of salts. During winter electrical conductivity was recorded higher (Table 5) which is attributed to a little mingling of freshwater influx from riverine stretch causing more concentration of ions. Dissolved oxygen (DO), Biological oxygen demand (BOD), and Free carbon dioxide had higher loadings downstream than upstream site, while chemical oxygen demand (COD) had almost similar annual average loading at both sites of Auranga estuary. Decreasing freshwater inflow, land field, anthropogenic sewage, and industrial runoff increases temperature, salinity, and growth of phytoplankton and during decomposition utilization of oxygen through the microbial activity during winter leading to maximum COD and low COD was observed during the monsoon season due to the presence of heavy river run-off, reduction of mixing of domestic and agricultural garbage, land-field drainage into the estuarine ecosystem and reduction of biological activity because of the decreased temperature and salinity. DO plays a vital role as a pivotal indicator of most of the biological, chemical as well as physical systems of the water hence it is considered as the significant variable of water quality [27]. Higher DO concentrations recorded during the winter season (Table 5) may be due to the combined effects of higher wind energy and the mixing of heavier rainfall and freshwater. Furthermore, the diversity of aquatic autotrophic components and their ability to produce oxygen may also be another important factor influencing the DO concentration. The periodic freshwater influx and the oxygen utilization by the microbial activities during winter give rise to the higher value of BOD. The maximum dissolved oxygen in February and November was also observed in the Timis river basin which ranked 1st quality, with a declined in August [27]. Silicate, potassium, and sodium had identical annual average contamination at both sites of the estuary. Ammonium, nitrate, and phosphate were similar at both sites of the estuary based on annual average concentration. Incorporation of anthropogenic sewage and agricultural fertilizers and influx from upper reaches lead to excessive inorganic phosphate during winter and summer periods. A high concentration of nitrate observed during the winter season might be due to the resultant freshwater draining, terra drainage, and fertilizers loadings from the nearby agricultural fields and oxidation of ammonia. Most of the nitrate might have been derived from the decomposition of organic wastes [4]. The variables such as temperature and DO showed a relationship with the seasonality, while the total suspended solids, turbidity, and nitrate were correlated with surface runoff caused by rainfall events [28]. In the developing nations, anthropogenic activities are the main sources of heavy pollution in many rivers. Several human activities such as discharges from effluents, agricultural chemicals utilization, over exploitation of water resources influenced the surface water quality. Several factors include total phosphorus, total nitrogen, nitrite and ammonium were the medium to serious scale pollutants in the Honghe river watershed, China [29]. In the case of heavy metal contaminations, Boron had a similar annual average concentration at both sites of Auranga estuary. Iron had higher annual average loading at the upstream site than downstream site during the study period. The water quality status of Zhaoquan River and Wailiao River was good, and Pangxiegou River and Qingshui River represented unsatisfactory water quality status [30]. The varifactors resultant from factor analysis indicated that the variables responsible for water quality changes are mainly associated to discharge and temperature (natural), organic pollution (point source: domestic wastewater) in relatively less polluted areas; organic pollution (point source: domestic wastewater) and nutrients (non-point sources: agriculture and orchard plantations) in medium polluted areas; and organic pollution and nutrients (point sources: domestic wastewater, wastewater treatment plants and industries) in highly polluted areas in the basin [31, 32].

	Color	Alkalinity	TDS	TSS	pH	Temperature	Free CO2	Salinity	Total hardness	Ca hardness	Turbidity	EC	Chloride	DO	BOD	COD	Phosphate	Nitrate	Ammonium	Sulphate	Sodium	Potassium	Silicate	Boron	Iron
Color	1
Alkalinity	0.47	1
TDS	0.64	0.79	1
TSS	0.33	0.90	0.51	1
pH	−0.87	0.32	0.56	0.17	1
Temperature	−0.70	0.45	0.64	0.40	0.76	1
Free CO2	0.81	0.88	0.85	0.77	0.64	0.71	1
Salinity	0.92	0.21	0.59	0.22	0.85	0.61	0.61	1
Total hardness	0.96	0.64	0.69	0.52	0.77	0.65	0.90	0.83	1
Ca hardness	0.93	0.52	0.61	0.35	0.76	0.84	0.78	0.85	0.95	1
Turbidity	0.89	0.30	0.64	0.40	0.91	0.57	0.62	0.22	0.80	0.87	1
EC	0.49	0.93	0.66	0.91	0.20	0.36	0.86	0.95	0.62	0.56	0.21	1
Chloride	0.98	0.56	0.73	0.42	0.85	0.76	−0.22	0.90	0.97	0.91	0.86	0.57	1
DO	0.86	0.83	0.81	0.70	0.71	−0.62	−0.42	0.68	0.47	0.88	0.72	0.81	0.90	1
BOD	0.85	0.76	0.74	0.59	0.75	−0.51	−0.41	0.70	0.21	0.92	0.79	0.71	0.86	0.97	1
COD	0.47	0.03	0.34	0.12	0.83	−0.63	0.26	0.55	0.31	0.32	0.68	0.22	0.46	0.30	0.37	1
Phosphate	0.93	−0.57	0.73	0.47	−0.33	−0.78	0.88	0.83	0.94	−0.83	0.74	0.63	0.97	0.86	0.77	0.30	1
Nitrate	0.86	−0.39	0.64	0.24	−0.68	−0.85	0.70	0.83	0.77	−0.71	0.88	0.25	0.86	0.73	0.74	0.83	0.76	1
Ammonium	0.39	0.25	0.01	0.38	0.73	−0.26	−0.01	0.51	0.71	−0.32	0.64	−0.41	0.30	0.12	0.27	0.88	0.10	0.66	1
Sulfate	0.52	0.99	0.82	0.86	0.34	0.46	0.70	0.48	0.69	0.60	0.37	0.94	0.61	0.87	0.80	0.13	0.62	0.40	−0.25	1
Sodium	0.34	0.48	0.18	0.57	0.03	0.49	0.48	0.12	0.42	0.45	0.08	0.58	0.40	0.35	0.15	0.31	0.58	0.93	−0.51	0.34	1
Potassium	0.45	0.16	0.41	0.31	0.07	0.17	0.34	0.55	0.47	0.68	0.15	0.32	0.47	0.32	0.22	0.29	0.60	0.66	−0.34	0.22	0.43	1
Silicate	0.26	0.06	0.20	0.10	0.60	0.77	0.23	0.23	0.13	0.13	0.28	0.14	0.30	0.15	0.11	0.80	0.25	0.11	0.55	−0.01	0.10	−0.40	1
Boron	0.76	−0.08	0.36	−0.32	−0.32	−0.45	0.31	0.92	0.59	0.45	0.91	−0.11	0.67	−0.42	−0.50	0.69	0.58	−0.73	0.75	0.02	−0.18	0.36	0.28	1
Iron	0.35	−0.86	−0.66	−0.89	0.18	−0.67	0.19	0.09	−0.48	0.26	0.59	−0.08	0.43	0.62	0.49	0.66	0.56	0.68	0.33	0.81	−0.63	−0.06	0.37	0.22	1

Table 4.

Correlation coefficient matrix of Physico-chemical parameters from Auranga estuary.

Seasons	Winter		Summer		Monsoon
	Downstream	Upstream	Downstream	Upstream	Downstream	Upstream
WOI	143.30	108.05	126.73	106.95	97.67	88.11
PI	1.41	0.97	1.18	0.94	0.88	0.78

Table 5.

Seasonal water quality index and pollution index from both sites of Auranga estuary.

Most of the component loadings were higher in downstream than the upstream site during the study period. In the case of seasonal variations, most of the variables were more in contamination during the winter season but some of the variables were more in concentration during summer (iron) and monsoon (total suspended solids and pH) seasons. The water quality improved a lot in the rainy season due to the dilution of estuarine water through the rainwater. The observation on poor water quality in downstream site than upstream was determined; it was poor grade water quality during winter also found in Yongjiang River, China [33].

Water quality index method can not only give the water quality rank, but also reflect the spatial and temporal variations of water quality condition. The worst water quality attributes to rapid population increase and fast industrial development, which causes the increase of wastewater discharge [34]. The water pollution in India has become a serious issue to economic, social sustainable development, not only because the imbalance between available scant water resources and dense population, but also the inefficient of water resources regulation and management. During the winter season, water quality was poor at both sites of Auranga estuary with more poor (143.30) and less poor (108.05) WQI at the downstream and upstream sites respectively. During the summer season, it was 126.73 for downstream and 106.95 for upstream that also indicates the poor water quality at downstream with medium poor water quality index value and also poor water quality at the upstream site but with less poor water quality index value. The water quality index was 97.67 for the downstream site and 88.11 for the upstream site during the monsoon season which proposed good water quality at both sites of this water body in monsoon season (Table 5). Certain WQI scales are the result of changed water quality due tothe wastewater from human activities, industrial establishments, agricultural resources and illegal waste disposal in the basin. The computed average WQI values for the Timok River during the period of 1990–2014 showed significant oscillations in water quality and indicated high level of water pollution with organic and inorganic substances [35]. This study highlighted based on the WQI and PI that the water quality of the Auranga estuary was poor in the winter and summer seasons due to more component contamination and good water quality in the monsoon season due to more freshwater influence because of the heavy rain.

The pollution indexes were 1.41 for the downstream site and 0.97 for the upstream site during winter that proposed medium polluted and slightly polluted water respectively of Auranga estuary during this season. During the summer season pollution indexes were 1.18 and 0.94 for downstream and upstream respectively that also indicate medium polluted and slightly polluted water. During the monsoon season, pollution indexes were 0.88 for the downstream and 0.78 for the upstream site which proposed slightly polluted water at both sites of this water body (Table 5). The main water pollution was originated from main two kinds of sources: the natural sources and the anthropogenic sources were associated with urban input, sewage, industrial dumps and surface runoff from agricultural areas [36].

There are mankind actions and demographic properties on one site and urban and partial industrial activities on another site, that is affected the water quality of the Auranga hydrographical basin. In this basin, the surface water resources and groundwater of this region are getting polluted by the main causes such as releasing of untreated wastewater from the industrial areas, domestic garbage, and pollutants from farming activities as well as animal farming activities. The human stress on the surface water within Auranga river catchments is induced by the total number of inhabitants (almost 51,410 people) from villages and the urban inhabitants (almost 1,53,271 people) from Valsad Municipality and Valsad Industrial notified area by census-2011 by the organic loading that they generate through the industrial activities, land use, and animal husbandry, and lastly the hydrographical system improvement through, as an outcome of mankind actions.

Based on the bi-monthly interval assessment, the component loadings were more in November and December. Some of the variables such as total dissolved solids, total suspension solids, chloride, temperature, electrical conductivity; sodium, and potassium were more concentrated in the months of March and April. The lowest contamination was found during the month of September and October during the study period because of the dilution of water due to the rainy season.

WQI gives important and objective information, and it is worth further promoting water quality inspections. It is a feasible method for evaluating the water quality conditions [30]. The water quality index over the year was 115.97 at downstream and 85.30 at upstream. The water quality status is poor (100–200) at the downstream site and good (50–100) at the upstream site according to the average annual loadings of the analyzed parameters during the study period. The values of the water quality index from these two stations correspond to the poor and good water class, which are influenced by the various variable, by the high values of the chloride, sulfate, alkalinity, iron, nitrate, DO, pH, COD, boron, temperature, phosphate, and TDS from the water of Auranga river estuary, as a result of the agricultural practices, municipal and industrial wastewaters, dumping site, manure from farms, and so on. The pollution index over the year was 1.09 (medium polluted) at downstream and 0.86 (slightly polluted) at upstream of Auranga river estuary. The water quality of the Auranga river estuary is influenced by many factors including the quantitative variation of biogenic and organic substances (Table 6).

Parameters	Index/ rank	Relative index (Wi)	Downstream (Site 1)		Upstream (Site 2)
			Quality rate (Qi)	Sub index (SI)	Quality rate (Qi)	Sub index (SI)
Chloride	1	0.0240	806.44	19.35	490.54	11.77
Sulfate	2	0.0487	280.11	13.64	223.00	10.86
Alkalinity	2	0.0487	192.67	09.38	107.75	05.24
Iron	2	0.0487	172.03	08.37	270.63	01.18
Nitrate	2	0.0487	151.80	07.39	127.00	06.18
Color	3	0.073	121.66	08.88	72.22	05.27
DO	3	0.073	111.20	08.11	74.40	05.43
pH	4	0.097	95.20	09.23	97.20	09.42
Boron	4	0.097	78.91	07.65	77.75	07.54
COD	4	0.097	57.35	05.56	59.30	05.75
Temperature	4	0.097	79.43	07.70	83.33	08.08
Phosphate	5	0.122	44.00	05.36	34.00	04.14
TDS	5	0.122	43.70	05.33	36.41	04.44
WQI				115.97		85.30
PI				1.09		0.86

Table 6.

Annual water quality index and pollution index from downstream and upstream of Auranga estuary.

Correlation is a univariate statistical tool that is used to compute the rating scale of interrelation between two variables [37]. This interrelation rating scale was calculated through correlation analysis from the values of the regiment of water quality variables of the study area. The correlations between various hydro-chemical parameters in the Auranga estuary are given in Table 4.

At the monitoring sections situated downstream of the wastewater discharge, high values of iron, phosphate, and nitrogen compounds have been identified, more exactly of the nitrate and ammonium ions, which influence the quality of the watercourses. Water pollution by nitrate and phosphate reaches quite higher levels due to the introduction of compact procedures of farming, with it more utilization of chemical manures and more numbers of creatures in limited areas, especially in animal farming complexes from the Auranga hydrographical basin. During the analyzed period (2019) the evaluation of the quality status of estuarine watercourses, existing within the Auranga hydrographical system has revealed the fact that the river has been found in good water quality status. The tendency of the water quality index is assessed by the pecuniary activities in the agriculture, industrial, and residential areas in the sampling stations’ vicinity in the Auranga hydrographical basin. For these reasons, constant monitoring is necessary, especially because this river flows further through the territory of Arabian Seawater.

4. Conclusion

The Water Quality Index of Auranga River Estuary ranges from 85.30 (Upstream) to 115.97 (Downstream) that indicates good water and moderate water quality respectively. The Pollution Index of water of Auranga Estuary ranges from 1.09 to 0.86 which indicates that the estuarine water is slightly polluted. The rapid industrialization and anthropogenic activities along the estuarine system and the coastal areas have brought a considerable decline in the water quality of the estuary. As per the bimonthly evaluation, contamination of components was higher in the months of November–December. Seasonal variation showed that most of the variables were more in contamination during the winter season. The water quality of Auranga estuary was slightly poor in the winter season due to more component loadings and good water quality during monsoon season because of more freshwater influence of heavy rain. Hence, the distribution pattern of nutrients in this estuary is controlled by many factors such as sewage from the industries, urban area, and agricultural sources, estuarine dynamics, fish processing unit, etc. During the analyzed period (2019) the evaluation of the water quality status of estuarine watercourses (rivers), existing within the Auranga hydrographical system has revealed the fact that the river has been found in good quality status. Awareness about anthropogenic pressure generated on water sources is necessary for the identification of the quality of water bodies and ultimately for adopting distinct methodology to protect and conserve the water in this region of Gujarat.

Acknowledgments

The authors gratefully acknowledge SHODH, Govt. of Gujarat for financial support.

Conflict of interest

The authors declare no conflict of interest.