Water quality analysis, treatment, and economic feasibility of water services of the Neora River in the fringe area of Neora-Valley National Park, India Open Access

Water quality of Indian rivers has worsened over time due to alarming levels of pollution and deteriorating water quality arising from various anthropogenic activities. Consequently, the Ganga River in Uttarakhand was reported to be vulnerable as well as the quality assessments on the rivers Mahanadi, Narmada and Gomti have depicted a considerable amount of contaminants in surface water (Rai et al. 2011; Hussain et al. 2020). The subsequent decrease in water resources may create a dispute over the supply of available freshwater (Shaban & Sharma 2007). Furthermore, extreme climate combined with an increase in agriculture, industrialization, urbanization, and water extractions has intensified the water shortage, especially in developing countries (Sinha et al. 2017). The acute water crisis is one of the central conundrums in Darjeeling Himalaya, owing to its adverse topographical features, deforestation, tourism, and climate change (Mondal & Roychowdhury 2019). Notably, the groundwater cannot be dragged economically in these hilly areas, which forces people to directly consume the river water (Singh et al. 2020). As a result, the Neora River is one of the fundamental water springs as well as the sole source of water for the whole Kalimpong town in Darjeeling. Hence, it is astute to assess the surface water quality at regular intervals for adopting an accurate water management plan. Many scientists (Othman et al. 2020) have conducted a wide range of investigations on water resources using the mathematical tool, the Water Quality Index (WQI), to simply compute a number to express the overall water quality at a certain place at a given time. The four important steps of WQI include the selection of parameters, a transformation of the parameters into unit-less values, weighting each parameter, and aggregation of the sub-index of each parameter to reach the final value (Abbasi & Abbasi 2012). It has been applied to assess the river water quality in various water resources (Miraj & Bhattacharya 2017; Bhatti et al. 2020).

In addition to assessing the water quality, contamination in the water needs to be treated downstream with various advanced disinfection methods to render it potable for human consumption. In this regard, electrochemical disinfection has attracted increased attention in recent years as an alternative to traditional chlorination. In electrochemical oxidation, due to the application of an electric current or a potential difference between two electrodes (anode and cathode), hydroxyl radicals or other oxidizing species can be generated, depending on the electrode material used and the type of supporting electrolyte used. Selection of the electrode material is always crucial for the efficacious performance of the electrochemical processes. Among all the available electrode materials, carbon is the most attractive due to excellent conductivity, economic feasibility, and chemical stability in comparison with dimensionally stable anodes (DSA) and boron-doped diamond (BDD) anodes (Hansen et al. 2010; Cao et al. 2013). Previously, carbon electrodes were coated with noble materials to boost the electrocatalytic activity in a similar manner, the present research was also taken up to assess the performance of a novel electrochemical oxidation reactor fabricated with tin-coated graphite electrodes in terms of disinfection efficiency as it is an economical and easy way for boosting the electrocatalytic activity (Yi et al. 2013).

Along with the optimum water quality, the quantity of water from the forest land also contributes to human life for both domestic and non-domestic purposes. The preferable method for quantification of water supply is the willingness to pay method (WTP), as it is a conceptually correct way to evaluate the value of water resources in terms of money (Griffin et al. 1995). Applying this method, the researchers estimated the value of about 3.42 US Dollars for open-source water in the Pavlodar Region, Kazakhstan (Tussupova et al. 2015) and around 8.03 US Dollars/decare for water quality betterment of Aksu River (Ikıkat Tumer 2020).

Therefore, the objective of the present study was to conduct the water quality analysis of river Neora as the river water is directly consumed by the rural population inhabiting the lower fringe of the park, and the pricing of water has also been taken into consideration for encouraging people to reduce water wastage which has not been carried out on the Neora River till date. Also, the present research aims to formulate an optimal water management policy regarding quality assessment, treatment, and economic feasibility of water services in River Neora, which may satisfy the future water demands of the villagers.

Surface water samples were collected from the Neora River for the estimation of six parameters, namely temperature, pH, total solids (TS), dissolved oxygen (DO), biochemical oxygen demand (BOD₅), and total coliform in starting point (Site 1), near hydel project (Site 2), near village Malchar (Site 3) and endpoint (Site 4) (Figure 1). The sampling locations were selected on the basis of field survey and geospatial techniques to account for the impact of dense forest cover, human settlements, light forest cover, and hydel projects on river water. The composite sampling method was used for each parameter except for DO and BOD₅. Water samples were kept in an icebox (≤4 °C) to abate microbial activity, which can tweak the biochemical properties of the water samples. The water sample for coliform estimation was collected in previously autoclaved 100 mL plastic vials.

The potential confounding variables that can affect the water quality parameters are the presence of metals and dissolved organic matter (DOM) in the water. In this regard, if metals are present in the water, they will react with the DO of the water and likewise microorganisms present in the water will consume DO for degrading the DOM thus depleting the DO of the water and ultimately deteriorating the water quality. However, the presence of the metals and DOM is more prevalent, where the water body is receiving the discharge from sewage treatment plants or industries. Since the river chosen for the study falls under the highly sensitive wildlife habitat area so probability of the river receiving the discharge from above mentioned sources is ruled out and thus the presence of DOM and metals in the river water was not considered during the study. Another confounding variable that can affect the water quality is the spatial variance while collecting the sample and for this, different locations along the river were identified to account for the spatial variance with respect to the stretch of the river. For accounting for the spatial variance with respect to the depth of the river, samples were drawn out from the mid-depth of the river by considering the fact that at mid-depth, rivers tend to have more mixed and homogenous conditions thus exhibiting the representative sample of the river.

All six water quality parameters were analyzed for the sample collected from Site 1, Site 2, Site 3, and Site 4. Temperature and pH were measured on the sampling spot with the aid of portable EUTECH PCTestr 35 (0.01 Accuracy), USA). TS, DO, BOD₅, and total coliform were analyzed with the standard method (Standard Methods for the Examination of Water and Wastewater 2012). The analysis was carried out three times and the average values of each parameter were taken.

The WQI is defined as the composite influence of individual parameters on the overall quality of the water. Since many parameters widen this index value; hence, the selection of parameters is imperative to calculate the WQI. The Weight Arithmetic Water Quality Index (WAWQI), the most used formula of the WQI has been coined by Brown et al. (1972). Six physicochemical and biological parameters namely temperature, pH, TS, DO, BOD₅ and total coliform were chosen based on the selection done by Brown et al. (1972) for calculation in this research. The WQI is helpful in adopting the management plan of water resources and the same has been applied in this study to compare the water quality at four sampling sites in the Neora River.

Here, q_n refers to the quality rating of nth water quality parameter; W_n refers to the unit weight of nth water quality parameter; V_n refers to the estimated value of nth water quality parameter at a given sample location; V_id refers to the ideal value for the nth parameter in pure water (V_id for pH = 7 and 0 for all other parameters); S_n refers to the standard permissible value of nth water quality parameter; K refers to the constant of proportionality.

Village Malchar, with a population of 455 located in the forest fringe, was selected purposively for this study as the inhabitants of this village were found to fetch water directly from River Neora for their regular use. Initially, a focus group discussion was performed with 42 respondents that appeared during the survey, using a questionnaire prepared with two divisions. The first part was structured to obtain the demographic characteristics of the respondents and the second part contained a number of close-ended questions to gather basic information regarding per-day household consumption, household water use practice, the current situation of water supply, water supply period, the status of water-related disease and household size (Wendimu & Bekele 2011).

The information generated from the focus group discussion aided in estimating the amount of money the villagers were willing to pay for a particular quantity of water by applying the WTP method. The hypothetical biases of data were eliminated by approaching ex-ante and ex-post survey strategies to the respondents (Loomis 2014). The ex-ante method includes a ‘Cheap talk’ where respondents assert about the hypothetical biases and the real-world consequences of response to decisions about the provision of goods and taxes that will be paid. However, ex-post actions are taken after the survey where WTP responses are calibrated using an uncertainty scale. Before asking the WTP questions, respondents are cautiously informed about the laboratory-tested value of bacterial contamination and its probable health effects. They were also provided a better understanding of river water supply to each household through a pipeline instead of direct water use which leads to the deterioration of water quality.

A linear regression analysis was done between collected WTP on water and household determinants to check the villagers' perception of WTP to maintain the water quality as mentioned in Table S2, Supplementary material.

Pearson's correlation helps to identify the most significant process parameter and its association with the other parameters, while analysis of variance illustrates the spatiotemporal variations and the causative external factors on water parameters (Bhat et al. 2014). Hence, Pearson's correlations (Shroff et al. 2015) and One-way ANOVA (Abinandan et al. 2014) were determined using SPSS software (Version 20) to estimate the linear relationships between the parameters and the seasonal variation of parameters, respectively. Before applying the ANOVA, a normality test was performed using a Normal Q–Q plot, and Shapiro-Wilk and Kolmogorov-Smirnov test to meet the normality assumption of ANOVA test results are provided in Figure S1 and Table S2, Supplementary material.

The water temperature of both pre-monsoon and post-monsoon in the years 2018 and 2019 were found to be low in all sampling spots, representing a good sign of higher DO (Table 2). This can be attributed to the fact that cold water can retain more DO than warm water (Walczyńska & Sobczyk 2017). The pH in all sites was within the recommended value of the World Health Organization (WHO). Though the value of TS in all sampling sites was within a permissible limit of WHO, during post-monsoon, the value of TS was comparatively higher than in pre-monsoon. The high TS content was also observed at the downstream of the river. The probable reason for higher TS during post-monsoon may be due to river discharge and land drainage brought about by monsoon rain into the river (Karim & Panda 2014). A good level of DO in each sampling site was observed with slight seasonal variation during pre-monsoon and post-monsoon, justifying it as a healthy water body to be used for all sorts of household and irrigation purposes. Low concentrations of BOD₅ and insignificant seasonal variation were observed in all sampling sites, representing that the water was free of organic pollution (Xu et al. 2020). The average value of total coliform was comparatively higher near Malchar village and downstream of the river rather than the other two sites owing to more anthropogenic activity (Seo et al. 2019).

Pearson's correlation coefficient measures the strength of the linear relationship between two variables. It has a value between −1 and 1, with a value of −1 meaning a total negative linear correlation, 0 being no correlation, and +1 meaning a total positive correlation. The temperature showed a significant positive correlation with pH, TS, and total coliform (Table 3). Secondly, the pH level also showed a positive correlation with TS present in the water. The TS was also positively correlated with BOD₅ and total coliform. The linear relationship between total coliform and TS can be attributed to soil erosion due to heavy water currents, and rainfall may be an influential factor for the positive significance between TS, and total coliform. Alternatively, DO showed a significant negative correlation with temperature and total coliform since a high temperature stimulates the growth of microorganisms, which in turn consume DO in water for aerobic decomposition. Finally, BOD₅ showed a positive correlation with total coliform (at a 5% level) as it indicates bacteriological contamination in water.

The ANOVA test allows a comparison of two or more than two groups at the same time to determine whether a relationship exists between them. One-way ANOVA analysis of water parameters showed significant variations (p < 0.05) in temperature, pH, TS, and total coliform in pre- and post-monsoon at a 5% level of significance (Table 4). The process parameter values of temperature, pH, TS, and total coliform have clearly supported the alternative hypothesis, which has suggested that the mean between the groups was totally different from one another. In ANOVA, the large values of F-statistics depicted that temperature is the strongest contributor in explaining the variation during pre-monsoon and post-monsoon, followed by TS, pH, and total coliform. Accordingly, it can also be assumed that the highest rainfall in this region may be a causative factor of seasonal variation of water parameters.

According to the Pearson correlation table, the low temperature in river water indicated the presence of clean water and low microbial activity (Singh et al. 2015). The near-neutral value of pH also represented a low concentration of TS, indicating that the river water was free from soil particles and microscopic plants and animals (Razman et al. 2023). Low BOD₅ value and high DO content were indications of a lower MPN index of total coliform in the water.

The WQI of all sampling sites of the study river in both pre-monsoon and post-monsoon for the years 2018 and 2019 have been given in Table 5. The status of river WQI ranged between ‘Excellent’ to ‘Good’ in the fringe area of NVNP, indicating the WQI of A and B grades, respectively. In 2018, the water quality with grade ‘A’ in Site 1 prevailed throughout the year owing to less anthropogenic interference and a dense forest cover over the region. In 2019, The WQI values showed the water quality with grade ‘A’ in pre-monsoon except Site 4, while water quality with grade ‘B’ during post-monsoon in all sites. In the case of seasonal variations, the water quality was relatively better in pre-monsoon than post-monsoon. An inferior water quality (grade ‘B’) during post-monsoon might be instigated by sediment encroachment due to prolonged monsoonal rain alongside a high-water current. Similar seasonal variations of water parameters were also observed in Loktak Lake in Manipur, India (Das Kangabam et al. 2017). The WQI also reveals that the water quality is deteriorating in successive years, especially near villages and downstream, probably due to an annual increase of human settlements, which intensifies the river water use and the diminution of the forest land at the end of the fringe area (Brogna et al. 2018).

Electrochemical processes have emerged as environment-friendly methods and sustainable technologies that offer different solutions to many environmental problems because they are versatile, efficient, cost-effective, can be easily automated, and the electrons are a clean reagent, inexpensive and suitable reagent to drive the decontamination, avoiding conventional chemical oxidizers or reducing agents (Sabatino et al. 2017). Moreover, the electrochemical oxidation process can be operated through sustainable renewable sources like solar power in villages, so these processes can be highly feasible in rural areas.

In the case of other advanced treatment methods like membrane filtration technology, the main challenge is the high cost of the membranes, and the fouling issue as it causes a reduction in permeate quality and filtration productivity and increases energy usage. Other drawbacks include the generation of membrane waste, which is problematic to dispose of (Algieri et al. 2022). On the other hand, in ultraviolet (UV) treatment, UV light has no post-treatment sterilization capability and can only eliminate the microbes present in the water during treatment. If the water is cloudy, pre-filter and UV systems require huge electricity. Also, high cost and constant high voltage AC electricity is required for UV operation. Low dosages may not effectively inactivate some viruses, spores and cysts. Organisms can sometimes repair and reverse the destructive effects of UV through a repair mechanism called photoreactivation (Gibson et al. 2017).

It was found that the electrochemical oxidation method was highly operative for treating water contaminated with coliform. A disinfection efficiency of 6 log removal of coliform was achieved within a contact time of 6 min at a current density of 2.5 mA/cm², whereas at the same current density, no change in disinfection efficiency was observed within a contact time of 3 min. When the current density was increased from 2.5 to 4 mA/cm², the same disinfection efficiency of 6 log removal of coliform was achieved within 2 min. In comparison with the conventional chlorination process, a contact time of at least 25 minutes was required to achieve a disinfection efficiency of 6 log removal of coliform (Table 6). Previous studies have already indicated that, at high current densities, oxygen evolution and formation of perchlorates occur (Bergmann & Koparal 2005; Badruzzaman et al. 2009). So, in the current investigation, the maximum current density was not raised beyond 4 mA/cm², whereas with respect to electrolysis time, at the same current density of 4 mA/cm² the maximum disinfection efficiency (6 log removal of coliform) was attained in just 2 min. Thus, it can be concluded that, with a disinfection efficiency of 6 log removal of coliform, all the cells in the treated water samples lost their cell viability from being biologically available for incubation.

The strong oxidants, such as hydroxyl radicals generated in the electrochemical oxidation process, attack the bacterial cell membrane and cell wall, leading to cell lysis. The high capacity of electrochemical disinfection may be attributed to the short-lived and energy-rich products with a more powerful germicidal capacity. Simultaneous monitoring of other parameters did not show any extensive changes in water pH or temperature during the treatment period, thus maintaining the system as an acceptable drinking water source.

Even though EO processes are found to be efficient in treating water, environmental impacts associated with this technology cannot be overlooked. This includes the requirement of energy and electrodes, which add to the carbon dioxide emissions during the life cycle. To overcome this barrier, integration of this technology with the available renewable source to fulfill the energy demand can prove effective in reducing the carbon footprint and waste-derived inexpensive durability electrodes need to be explored to make this technology more environment friendly.

All the inhabitants of Village Malchar have collected water directly from the Neora River for many generations for domestic and non-domestic purposes. The average quantity of water used for domestic purposes was estimated at 32 L/capita/day in the area, which resembled the average water use value of 20–40 L/capita/day in rural Africa (Wallingford 2003). The annual consumption of water from the river for domestic and non-domestic purposes was calculated to be 5,314,400 and 1,470,000,000 L/yr, respectively, leading to a total water requirement of about 1,475,314,400 L/yr (Table 7).

The computed value of water utilization (1,475,314,400 L/yr) for domestic and non-domestic purposes revealed the greater dependency of villagers on River Neora owing to the ease of water availability and good water quality of the river. A similar study has revealed that riparian communities were dependent on the White Volta River in Northern Ghana to fulfill their regular water needs due to good quality of water availability throughout the year (Mul et al. 2018). The dependency of villagers on the river water made them more conversant about the river.

The survey showed that more than half of the interviewers (74%) were interested in paying for the sustainable water supply from the Neora River. Among all, 26% of the respondents strongly disagreed with paying for water. The maximum proportion of the respondents (24%) was willing to pay 0.36 US Dollars and about 19% of respondents were willing to pay 0.48 US Dollars per month. Around 10% of respondents were found to pay 0.12 US Dollars and 14% of respondents were willing to pay 0.24 US Dollars per month. The lowest proportion of respondents (7%) was willing to pay 0.60 US Dollars per month to maintain the regular water flow. The average WTP of respondents for domestic water use was obtained to be 0.36 US Dollars per month. The calculated value of WTP per cum of water was 0.060 US Dollars for domestic use. The total estimated value of water for domestic purposes was 318.13 US Dollars per year. On the contrary, the economic value of water used for non-domestic purposes was estimated to be 17.96 US Dollars per year. The total monetary value of water for domestic and non-domestic purposes was 695.29 US Dollars (Table 8).

During the interview, many of the respondents showed interest in paying for water to maintain the river water supply. However, the rest of the respondents were found to be a bit hesitant to levy the WTP on water in terms of rupees per month, possibly due to their financial constraints. Around 74% of respondents were observed to show interest in levy charges on water, stating their knowledge about the value of river water and their concern regarding the maintenance of water supply. The calculated average WTP per month (0.06 US Dollars per cum) of domestic water was comparable with the mean WTP of 0.038 US Dollars per cum of municipal water in Calcutta (Majumdar & Gupta 2009). However, this outcome is in incongruity with the study conducted by Venkatachalam (2015) where the estimated WTP is 0.23 US Dollars per cum. This lower value of WTP reflects the financial constraint of the villagers in Malchar village. Despite this, the respondents showed their awareness toward the maintenance of good water quality of River Neora as they do not have other facilities of freshwater resources to meet their daily needs. The monetary value of water for domestic purposes (318.13 US Dollars/year) represented the respondents' awareness to encourage sustainable water use for the future as there was no other water source to fulfill their regular water demand other than the Neora River.

The regression coefficients represented a positive linear relationship shown by household size, education and monthly income of villagers with WTP at a 95% confidence level (p value < 0.05). These outcomes clearly designate the probability of interest on WTP increases with the increase in monthly income and household size. This result is supported by the study conducted by Nam & Son (2005) in Ho Chi Minch City, Vietnam. The socioeconomic variables include household size, age of respondents, education level, occupation of respondents, and their monthly income except gender as all respondents were found to be males during the survey. Besides, the educational qualification of respondents has directed enough knowledge of respondents on current status of water quality and they can perceive water as a priced commodity (Gondo et al. 2020). However, age and occupation did not show any statistical significance with WTP signifying that all the age groups and the respondents with different occupations are equally concerned about the better water supply and quality. This finding is consistent with the study on the improvement of drinking water quality in Songzi, China (Jianjun et al. 2016).

The estimated value for non-domestic water use (377.16 US Dollars/year) specified that the water resource of The Neora River saved villagers' expenditure on irrigation water cess. Water pricing for irrigation may have some negative impacts on poor farmers, such as compelling farmers to adjust their plowing decisions and lessen their water use for cultivation, which consequently leads to a decline in their earnings. To compensate for such adverse effects of water pricing, the government should implement an agricultural subsidy to supplement farmers' income and to manage the supply of agricultural commodities. The economic value of water (695.29 US Dollars/year) was calculated based on water utilization and the agricultural area, which can contribute to future policymaking. This outcome was in conformity with the study in the transboundary Buna River Region, Albania by Grazhdani (2013).

The comprehensive investigation showed the congruity of the Neora River water in the forest fringe of NVNP for both domestic and non-domestic purposes. Relatively better water quality at the starting point of the fringe area reveals the capability of an eco-sensitive area to maintain good quality and flow of the naturally produced river water. Determination of WTP on water is essential to record the information pertaining to villagers' financial weakness and priorities for the storage of freshwater resources. The responses of villagers have shown quite surprising results compared to other developing nations, where people are least concerned about paying due to their underprivileged socioeconomic condition. The economic value (695.29 US Dollars per year) of the Neora River water clearly designates it as a crucial source of water for local tribes residing in Malchar village. To maintain the drinking water quality standards, the water on the downstream side was treated with an electrochemical oxidation batch reactor. The strong oxidants generated in the electrochemical oxidation process, attacked the bacterial cell membrane and cell wall, leading to cell lysis and resulting in the 100% disinfection of the water. The current density and electrolysis time played a major role in achieving this disinfection thus optimization of these two parameters is of much significance for attaining the higher disinfection efficiency. Conclusively, this finding provides some necessary implications for the government and policymakers to adopt a water management policy along with the local people's consent to uphold the good water quality of the Neora River for the forthcoming years. Moreover, governments should consider the villagers' socioeconomic determinants while designing any policy or projects on water service.

Authors' gratitude goes to the Head of the Department of Environmental Studies, NEHU, Shillong and the Department of Environmental Science and Engineering, IIT (ISM) Dhanbad, Jharkhand. The authors are thankful to the respondents of Malchar village. SM acknowledges the University Grant Commission for funding.

Data cannot be made publicly available; readers should contact the corresponding author for details.

The authors declare there is no conflict.