A coherent approach of Water Quality Indices and Multivariate Statistical Models to estimate the water quality and pollution source apportionment of River Ganga System in Himalayan region, Uttarakhand, India

Spatiotemporal and vertical variability of water quality in lentic small water bodies: implications of varying rainfall and land use conditions

Lentic small water bodies (LSWBs) deteriorate owing to anthropogenic activities, such as untreated domestic and agricultural waste disposal. Moreover, different turnover mechanisms occur during different seasons, contributing to nutrient enrichment and consequent degradation of LSWBs. However, understanding their spatial, temporal, and vertical variations during different seasons is understudied. In addition, studies on the variation in water quality under varying rainfall and land-use conditions are limited. Therefore, in this study, three LSWBs located in Northern India were studied during the pre-monsoon and monsoon seasons (December 2022 to October 2023). Total nitrogen (TN), chlorophyll-a (Chl-a), total phosphorus (TP), temperature, pH, dissolved oxygen (DO), total dissolved solids (TDS), chemical oxygen demand (COD), secchi disk depth (SDD), and water level (WL) were measured monthly. Sentinel-2 and CHIRPS pentad data were used for land use, land cover classification, and rainfall analysis. The spatial analysis indicates that the seasonal shift affects the water quality distribution, especially near the inlets and at the edges. The overall concentrations of TN and TP decreased during the monsoon season; however, they increased significantly at the inlets of the LSWBs. On the other hand, the Chl-a concentration shifted towards the edges due to the inflow during the monsoon. Temporal analysis also suggests that the arrival of the monsoon lowers pH, DO, and TDS. However, the concentrations of TN and TP increased because of agricultural runoff. Chl-a and COD show distinct variations due to the individual LSWBs' local conditions. Vertical variability analysis demonstrated pH, temperature, and TN stratification during the pre-monsoon period. However, during the monsoon, stratification is less significant due to intermixing. Redundancy analysis (RDA) showed that land use and rainfall patterns affected the water quality of LSWB 1, 2, and 3 by 53.49%, 81.62%, and 92.64%, respectively. This shows that land use, land cover, and rainfall changes affect the water quality of LSWBs. This study highlights the negative impact of runoff from agricultural land use as the main factor responsible for increased nutrient levels in the LSWBs.

Assessment of potentially toxic elements in groundwater through interpolation, pollution indices, and chemometric techniques in Dehradun in Uttarakhand State

Providing safe drinking water for the entire world's population is essential for ensuring sustainable development. The presence of harmful compounds in aquifers, majorly toxic elements, is a serious environmental concern around the globe. This research aimed to quantify for the initial period the amounts of toxic elements in freshwater in the Dehradun Industrial Region of Uttrakhand, India, as well as the associated health risks. The PTEs (potentially toxic elements) Fe, Cd, Mn, Cu, Cr and Pb, Zn, Ni is measured by AAS and compared to BIS and WHO requirements for drinking safety. The order of mean trace element values in all groundwater samples were determined as Fe > Zn > Cu > Ni > Co > Cd > Pb. HPI was discovered to be higher than high class during the research period (HPI > 30), but under the severe contamination criterion of 100. Iron's MI and PI values were consistently over the threshold limit during the research period, and certain toxic elements were discovered exceptionally near the threshold limit, indicating a severe future influence on groundwater quality. According to PCA (principal component analysis), CM (correlation matrix), and potential health hazard, maximum levels of toxic elements in groundwater in the Dehradun region are attributed to land use patterns, anthropogenic activity, industrial activity, fertilizer and pesticide leaching, and residential waste into the aquifer system. The findings of this study could aid local planners and policymakers in preventing health risks from contaminated aquifers through the deployment of suitable monitoring and mitigation measures.

Impact of industrial hotspots on Tamla nala and Nunia nala confluence - a tributary of the Damodar river

Clean water is essential for drinking, household use, and agriculture. Researchers studied 39 sites near Tamla nala and Nunia nala channels in Durgapur and Asansol City (West Bengal) to assess the deterioration level of water due to industrial discharge. During the first phase out of three, the researchers conducted a spatial representation of various physicochemical parameters, such as temperature, pH, Total Dissolved Solids (TDS), Total Suspended Solids (TSS), Total Hardness (TH), Electrical Conductivity (EC), Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), significant anions such as chloride (Cl-), nitrate (NO3-), phosphate (PO4-3), sulfate (SO42-), cyanide (CN-1) and fluoride (F-), as well as heavy metals/metalloids such as lead (Pb), cadmium (Cd), chromium (Cr), iron (Fe), copper (Cu), nickel (Ni), mercury (Hg) and arsenic (As). As observed the parameters at various sites along the stream exceeded threshold limits majorly due to industrial discharge: highest pH, TDS, TH, EC, Cl-, SO42- at site 26; Fe at site 1, TSS, COD, CN- at site 33, 31, 2 respectively; Cd, Ni, Cu at site 19; Hg and Pb at site 3 and As at site 20. Contaminated areas were marked in red and secure areas in green. Additionally, the HMPI (Heavy metal pollution index) was estimated for eight locations to understand the impact of heavy metal pollution in the second phase of the study. An extremely high HMPI indicates heightened toxicity and health risks for both residents and outsiders. The Canadian Water Quality Index (1.0) was calculated for eight sites in the third phase based on seventeen parameters. The resulting WQI value was below 44, indicating poor water quality at the sites. Due to the poor quality and critical heavy metal toxicity, the authors recommended continuous monitoring, strict regulation enforcement, increased treatment capacity, Zero Liquid Discharge implementation, and raising awareness among residents.

Heavy metal contamination assessment and potential human health risk of water quality of lakes situated in the protected area of Tisa, Romania

Protected areas are significant due to the high value of natural resources they shelter. This study's primary objective is to assess the quality status of the water resources (13 lakes and Tisa River) localized in the protected area of Tisa River on the territory of Romania. A number of 13 lakes and surface water (Tisa River) situated in the protected area through the Natura 2000 ecological network are studied. The chemistry and potential pollution status were analyzed by measuring and analyzing a set of twenty elements and sixteen physico-chemical parameters. The potential impact of anthropogenic activities was settled through the applied analysis and obtained results. A potential human health risk was noticed. Results indicated that waters are rich in Ni and Fe probably due to interaction with groundwater rich in Fe and Ni. Waters are characterized by potential contamination, which if directly or through the food chain consumed could negatively influence the human health. Piper and Gibbs plots indicated that the studied waters are divided into three categories based on water-rock interactions: mixed Ca2+-Na+-HCO3-, CaCO3-, and Na+-HCO3-. Likewise, the applied pollution indices (Heavy metal Pollution Index, HPI and Heavy metal Evaluation Index, HEI) indicated three pollution categories correlated to the As, Ni and Fe amounts. The findings of this research imply that the chemistry of the studied lakes and surface waters is influenced by the geogenic origin and emergence of anthropogenic activities. The significance of this research is related to understanding of mechanisms that influence the water quality, improving and conserving the natural water resources, and correspondingly understanding if any potential human health risks could be identified.

Unravelling groundwater contamination and health-related implications in semi-arid and cold regions of India

Groundwater, a vital global resource, is essential for sustaining life and various human activities. However, its quality and availability face increasing threats from both natural and human-induced factors. Widespread contamination, arising from both natural origins and human activities such as agriculture, industry, mining, improper waste disposal, and wastewater release, poses significant risks to human health and water security. India, known for its dense population and pronounced groundwater challenges, serves as a prominent case study. Notably, in most of its regions, groundwater resources have been found to be severely contaminated by various chemical, biological, and radioactive contaminants. This review presents an examination of contamination disparities across various states of semi-arid and cold regions, encompassing diverse assessment methods. The studies conducted in semi-arid regions of North, South, West, and East India highlight the consistent presence of fluorides and nitrates majorly, as well as heavy metals in some areas, with values exceeding the permissible limits recommended by both the Bureau of Indian Standards (BIS) and the World Health Organization (WHO). These contaminants pose skeletal and dental threats, methemoglobinemia, and even cancer. Similarly, in cold regions, nitrate exposure and pesticide residues, reportedly exceeding BIS and WHO parameters, pose gastrointestinal and other waterborne health concerns. The findings also indicated that the recommended limits of several quality parameters, including pH, electrical conductivity, total dissolved solids (TDS), total hardness, and total alkalinity majorly surpassed. Emphasising the reported values of the various contaminant levels simultaneously with addressing the challenges and future perspectives, the review unravels the complex landscape of groundwater contamination and its health-related implications in semi-arid and cold regions of India.

Evaluation of groundwater quality by adopting a multivariate statistical approach and indexing of water quality in Sagar Island, West Bengal, India

In the vicinity of the coast, predominantly groundwater is the sole reliable resource for potable purposes as the surface water sources are highly saline and unfit for human consumption. However, the groundwater in Sagar Island is highly vulnerable to saltwater intrusion. The majority of drinking water comes from government-owned hand pump-equipped tube wells. But during the summer season, many of these tube wells yield significantly less water. Hence, in the current scenario, water quality assessment has become important to the quantity available. Total of 31 samples of deep tube wells (groundwater) are collected at variegated locations during pre-monsoon season throughout Sagar, and then, the physical and chemical quality parameters of these water samples are analysed. Furthermore, a multivariate statistical technique is executed with the aid of the SPSS program. The hydro-chemical parameters that are taken into account for the quality analysis are pH, salinity, electrical conductivity (EC), total dissolved solids (TDS), total hardness, aluminium, arsenic, bi-carbonate, cadmium, iron, chloride, copper, chromium, cobalt, lead, magnesium, manganese, nickel, potassium, sulphate, zinc, and sodium. Then, the analysed data evaluates the water quality index (WQI). Five components are identified through the principal component analysis (PCA) technique, and 82.642% total variance is found. The outcomes of the quality assessment study illustrate that about 54.84% of collected samples come in the "excellent" water quality class when calculated by the "weighted arithmetic WQI method," and 90.32% of collected groundwater samples come in the "good" water quality class when computed using the "modified weighted arithmetic WQI method." This study helps for the interpretation of WQI to assess groundwater quality.

Mapping and assessment of river water quality under varying hydro-climatic and pollution scenarios by integrating QUAL2K, GEFC, and GIS

Water quality modelling has proved to be effective method for managing river water quality. But the most effective and comprehensive approach involving integration of river water quality simulation and pollution visualization with the objective of pollution reduction and maintenance of environmental flow strategies has gained less attention. Thus, the objective of this study was to employ an integrated approach for mapping and analysing river water quality under various hydro-climatic and pollution scenarios. Specifically, this approach involved the integration of a river water quality simulation model, QUAL2K, Global Environmental Flow Calculator (GEFC), and Geographical Information System (GIS) to develop water quality index (WQI) based map charts of water quality. The calibrated QUAL2K model was utilized to simulate WQI parameters including water temperature, pH, electrical conductivity, dissolved oxygen (DO), biological oxygen demand (BOD), nitrates (NO3), ammonia (NH4), and alkalinity. To analyse the WQI, the Weighted Arithmetic-Water Quality Index (WA-WQI) method was employed for various individual and combined pollution scenarios, environmental flow (Eflow), and climate change scenarios. The developed integrated approach was applied to the Bhadravati segment of Bhadra River, India. The findings revealed that the prevailing WQI status of the study stretch ranged from poor to unsuitable for drinking purposes. This deterioration can be attributed to the impact of both industrial and municipal effluents. By maintaining the effective Environmental Management Class (EMC) flow rates (class C flowrate of EMC (40.32 m3/s)) in conjunction with appropriate Pollution Reduction (PR) level (10% PR) at headwater and incoming drains, the stream self-purification capacity was enhanced resulting in the Bhadravati River stretch water quality transitioning to favourable water quality condition.

Spatiotemporal evaluation and assessment of shallow groundwater quality for irrigation of a tropical coastal groundwater basin

The present study aims at analyzing groundwater quantity and quality simultaneously to identify its availability and suitability for irrigation. Various water quality indices were used to assess (i) origin of the groundwater sources (Gibbs diagram); (ii) salinity, alkalinity, and sodium hazard (sodium adsorption ratio, exchangeable sodium percentage, Kelly's ratio, US Salinity Laboratory diagram, Wilcox diagram); (iii) magnesium hazard (magnesium absorption ratio); (iv) carbonate and bicarbonate hazard (residual sodium carbonate); (v) hydro-chemical facie and evaluation (Piper diagram and Expanded Durov diagram); and (vi) statistical relationship among the variables, sample sites, and spatiotemporal grouping (principal component analysis and cluster analysis). The overall objective is to quantify the irrigation suitability of groundwater reserves. Gibb's diagram suggests that the groundwater quality is mainly controlled by rock-water interaction. Piper trilinear showed the presence of various types of hydro-chemical facies such as Ca-Mg-HCO3, mixed, and sodium bicarbonate. The expanded Durov diagram revealed the hydro-chemical evolution, grouping, and areal distribution of the groundwater samples. USSL diagram, Wilcox diagram, Kelly's ratio, magnesium hazard, and permeability index suggest that the groundwater quality is suitable for irrigation. Kaiser-Meyer-Olkin (KMO) and Bartlett's tests confirmed the applicability of principal component analysis (PCA), which indicates that groundwater quality is controlled by rock-water interaction mainly. It also suggests that the groundwater has carbonate dissolution, which indicates the groundwater's hardness increased. Cluster analysis (CA) from the year 2000 to 2010 shows 4 to 8 groups present within the study area. Irrigation water quality suitability map and predicted groundwater potential zone map together act as a master tool for deciding tube well location, pumping schedule, and crop planning for the sustainability of the agriculture eco-system in the study area. The implementation of the aforementioned activities in the study area will further stop the advancement of the seawater intrusion front. The methodology shows the potential applicability for similar coastal groundwater basins worldwide with or without modification.

A review of the effects of environmental hazards on humans, their remediation for sustainable development, and risk assessment

In the race for economic development and prosperity, our earth is becoming more polluted with each passing day. Technological advances in agriculture and rapid industrialization have drastically polluted the two pillars of natural resources, land and water. Toxic chemicals and microbial contaminants/agents created by natural and anthropogenic activities are rapidly becoming environmental hazards (EH) with increased potential to affect the natural environment and human health. This review has attempted to describe the various agents (chemical, biological, and physical) responsible for environmental contamination, remediation methods, and risk assessment techniques (RA). The main focus is on finding ways to mitigate the harmful effects of EHs through the simultaneous application of remediation methods and RA for sustainable development. It is recommended to apply the combination of different remediation methods using RA techniques to promote recycling and reuse of different resources for sustainable development. The report advocates for the development of site-specific, farmer-driven, sequential, and plant-based remediation strategies along with policy support for effective decontamination. This review also focuses on the fact that the lack of knowledge about environmental health is directly related to public health risks and, therefore, focuses on promoting awareness of effective ways to reduce anthropological burden and pollution and on providing valuable data that can be used in environmental monitoring assessments and lead to sustainable development.

Development of water quality index as a tool for urban water resources management

Urban stream monitoring programs rarely consider the daily cycle of water quality. Furthermore, water quality indexes (WQIs) often rely on an excessive number of correlated parameters. To the best of our knowledge, no previous study used both the principal component analysis (PCA) and the daily cycle of the water quality of urban streams to create better WQIs. In this context, the present study aimed to develop a novel urban WQI (WQIurban) considering these two factors. Moreover, the main WQI in Brazil for water quality assessment for public supply (WQIcetesb) was used as a starting point (parameters: total solids (TS), temperature, turbidity, biochemical oxygen demand, pH, dissolved oxygen (DO), total nitrogen, total phosphorus, and thermotolerant coliforms (Escherichia coli)). The selected parameters to integrate the WQIurban received weights according to their importance for the conformation of water quality and a quality value was assigned to each parameter as a function of its concentration or measure. The developed WQIurban (parameters: pH, TS, E. coli, and DO) was able to maintain the seasonal and daily patterns of the urban stream water quality compared to the WQIcetesb. Nevertheless, the spatial relationship among the sampling sites was somewhat lacking. Our findings can help environmental managers, policy planners, and local researchers to improve their urban stream monitoring programs, saving money, time, and resources. Moreover, the WQIurban can be helpful during exceptional circumstances in which the water quality of urban streams must be quickly assessed.

Spatial water quality assessment of a mountain stream in northwestern India using multivariate statistical techniques

The water quality of Himalayan rivers and streams is deteriorating due to multitude of anthropogenic and natural influences and the changes are more pronounced in smaller hill basins with high human influx. Inadequate data and lack of monitoring further exacerbate the situation. The surface water quality of one such hill stream, Neeru was evaluated for potability and irrigation quality. The water quality parameters were analysed at 25 sampling stations over a stretch of 30 km across four seasons during a 2-year study from January 2014 to December 2015. The CCME Water Quality Index (WQI) indicated excellent water quality in upstream stations, while the midstream and a few downstream stations revealed varying degrees of impaired water quality. Although the irrigation quality of the stream was excellent, pollution levels near urban areas were rather high, necessitating considerable treatment for human consumption. The factor analysis yielded seven components with Eigenvalues greater than one that accounted for 83.656% of the variance and enabled the grouping of selected parameters based on comparable characteristics. The hydrogeochemical characteristics of the water samples indicated that they lie within the zone of rock dominance, while the trilinear diagram depicted the Ca-bicarbonate rich stream water. The study concluded that the upstream stations revealed pristine water quality, which significantly degraded towards human settlements. It thus calls for regular and long-term monitoring of the surface water quality to ensure the continuous and sustainable use of this important water body.

Hydrochemical characterization of groundwater quality using chemometric analysis and water quality indices in the foothills of Himalayas

Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic process. To analyse the spatial-temporal variation and pollution source identification and apportionment, the dataset was subjected to a globally acknowledged coherent technique using water quality indices and chemometric techniques (principal component analysis (PCA) and cluster analysis. The bulk of the samples tested were below the BIS's permissible levels. Groundwater samples from the pre- and post-monsoon seasons mostly contained the anions HCO- 3 > Cl- > SO2- 4 > NO- 3, while the primary cations were Ca2+ > Mg2+ > Na+ > K+. Groundwater was alkaline and hard at most of the sites. According to hydro-geochemical facies and relationships, Piper diagrams, and principal component analysis, weathering, dissolution, leaching, ion exchange, and evaporation were the key mechanisms influencing groundwater quality. The hydrochemical facies classified the groundwater samples into the Ca-Mg-HCO3 type. For all the sampling locations, PIG was determined to be 0.43, 0.52, 0.47, 0.48, 1.00, and 0.70; respectively. The majority of the test locations fell into the low to medium contamination zone, as determined by the groundwater pollution index (PIG) and contamination index. Three principal components, which together account for 93.8% of the total variance, were identified via PCA. The study's findings confirm the value of these statistical techniques in interpreting and understanding large datasets and offering reliable information to reduce the time and expense of programmes for monitoring and evaluating water quality.

Multidecadal assessment of environmental variables in the river Ganga for pollution monitoring and sustainable management

The Ganga River is the major source of drinking water for humans over the decades. It is also the ecological niche for millions of relict species, i.e., for a variety of planktons, benthic organisms, fish, and various other aquatic organisms. The blasting population resulted in an enhanced rate of pollution in the river system emanating from various anthropogenic activities and industrialization in the bank of river Ganga. The study was made in the middle and lower stretch of the river to monitor the decadal changes in the water quality of river Ganga from 1960 to 2019 at six different study sites. In the present study, various water quality parameters such as dissolved oxygen, pH, free carbon dioxide, total alkalinity, conductivity, total dissolved solids (TDS), hardness, chloride, and nitrate have been studied during 2015-2019. The data for 1960 to 2006 were taken from ICAR-CIFRI publications. Based on the studied parameters, National Sanitation Foundation (NSF)-water quality index (WQI) was calculated. In the present study, it was found that the calculated NSF-WQI was 69.24 in 1960-1961 which increased up to 113.39 during 2001-2006. But, with the implementation of various rejuvenating strategies, the WQI of the river got reduced to 106.48 during 2015-2019. This reflected the positive changes in the riverine system. Different water quality parameters such as dissolved oxygen, pH, and hardness were observed mostly within the permissible range as based on the drinking water guidelines for humans and survival of the aquatic organisms as well, except a few location-specific observations.

Water quality assessment in the ecologically stressed lower and estuarine stretches of river Ganga using multivariate statistical tool

Water quality of the Ganga River system is changing day by day due to multifold increase in population, especially near the banks of river Ganga, and associated exponential amplification of anthropogenic activities also played a remarkable role in it. The ecologically important lower and estuarine stretch of river Ganga comprising 7 different sampling stations, i.e., Jangipur, Berhampore, Balagarh, Tribeni, Godakhali, Diamond Harbour and Fraserganj, were selected for the study as the stretch is enriched with the vast number of floral and faunal diversity. The study was conducted for a period of 5 years, i.e., from 2016 to 2020. In the study, various analytical tools and techniques were used for the assessment of riverine water quality, i.e., for calculation of water quality index (WQI); The National Sanitation Foundation Water Quality Index (NSF-WQI) and the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) were used for the assessment. Along with WQI various statistical univariate as well as multivariate analytical tools like principal component analysis, correlation, ANOVA, and cluster analysis were also used to achieve the desired outputs. In the study, it has been observed that NSF-WQI varied from 61 to 2552, in which the higher value of NSF-WQI denoted the unsuitability of the water quality concerning the drinking water standards and vice versa. The CCME-WQI represented a similar trend as that of NSF-WQI, as it varied from 18 to 92 in which the lower value denoted degradation in the drinking water quality and vice versa. The study revealed that the Diamond Harbour-Fraserganj stretch is having an undesired level of water quality which were analyzed based on the drinking water guideline values of the Bureau of Indian Standards and that of NSF-WQI and CCME-WQI.

Multi-step ahead prediction of hourly influent characteristics for wastewater treatment plants: a case study from North America

Prediction of influent characteristics, before any treatment takes place, is of great importance to the operation and management of wastewater treatment plants (WWTPs). In this study, four machine-learning models, including multilayer perceptron (MLP), long short-term memory network (LSTM), K-nearest neighbour (KNN), and random forest (RF), are introduced to utilize real-time wastewater data from three WWTPs in North America (i.e., Tres Rios, Woodward, and one confidential plant) for predicting hourly influent characteristics. Input variables are selected using an autocorrelation analysis and a variable importance measure from RF. Both univariate and multivariate analyses are investigated to improve model accuracy. The performances of one- and multiple-step-ahead models are compared. With a short prediction horizon, all the models derived from both univariate and multivariate analyses show excellent performance. It was found that the performance deterioration as the prediction horizon expands could be mitigated significantly by including extra variables, such as meteorological variables. This work can provide valuable support for the high-temporal-resolution prediction of wastewater influent characteristics for WWTPs. The proposed models can also bridge the gap between data and decision-making in the wastewater sector.