Integrated Water Quality Index Research Articles

Assessment of Climate Change Impacts on Hydrology Using an Integrated Water Quality Index

Traditional Water Quality Indices (WQIs) often fail to capture the significant impact of flow velocity on water quality, especially under varying hydrological conditions. In this study, an Integrated Water Quality Index (IWQI) was developed by combining water quality parameters and flow rate, providing a more comprehensive assessment under various flow conditions. Compared to traditional indices, the IWQI showed slightly lower correlations in individual parameter performance, but it performed well in evaluating water quality changes associated with flow variations. Parameters such as Total Phosphorus (TP), Total Coliforms (TC), and Fecal Coliforms (FC), which are prevalent pollutants in the Cheongmi River, significantly influenced IWQI scores. River water quality was evaluated using input data simulated under a climate change scenario. When precipitation was abundant, the IWQI score remained relatively stable even with reduced flow rates. However, during periods of insufficient rainfall, water quality deteriorated sharply. While general water quality parameters exhibited approximately a 10% change as flow decreased, TC and FC showed rapid deterioration, with change rates ranging from 20% to 60%. These findings underscore the importance of managing TC and FC, particularly when insufficient rainfall is predicted, as they are major sources of pollution.

Evaluating water, sanitation, and hygiene in schools of Bangladesh: progress toward SDG compliance

ABSTRACT The availability of safe water, sanitation, and hygiene (WASH) facilities in schools is essential for a healthy learning environment and achieving sustainable development goals (SDGs) 4 and 6. Despite its importance, comprehensive studies on drinking water quality, sanitation, and hygiene in schools are scarce. This study explicitly assessed the WASH services and gaps in 43 educational institutions, located in Tongi, Bangladesh, through field and laboratory investigations. Thirteen physicochemical and bacteriological parameters were analyzed, and water quality was classified using an Integrated Water Quality Index (IWQI). Hygiene and sanitation were evaluated through observations and data from school administrators on water sources, toilets, handwashing facilities, and solid waste management. Results showed that WASH services exceeded the national average, but all schools had dangerously high Escherichia coli levels (mean: 43.95 CFU/100 mL) in drinking water, posing health risks. Additionally, 89.72% of samples showed elevated manganese levels, 35% had high iron, and 41.86% had increased conductivity. About 35% of water was unsuitable for drinking based on IWQI. Schools lacked the capacity to monitor WASH quality, especially drinking water. A strategic framework for safe WASH facilities is recommended. The findings can lead the policymakers to prioritize the improvements in WASH facilities for attaining SDG 6.

Groundwater geochemistry using modified integrated water quality index (IWQI) and health indices with special emphasis on nitrates and heavy metals in southern parts of Tirupati, South India.

Groundwater is particularly vulnerable to pollution in places with a high population density and extensive human usage of the land, especially in southern parts of Tirupati, India. To assess this, 60 bore-well samples were obtained and assessed for physical specifications, ion chemistry, and heavy metals during the pre- and post-monsoon seasons 2022. The current investigation employed a modified integrated water quality index (IWQI), conventional graphical and human health risk assessment (HHRA) of nitrates and heavy metals to know the groundwater chemistry and its detrimental health effects on humans. The major ions were analyzed using American public health association (APHA)standards, whereas heavy metals were analyzed using inductively coupled plasma optical emission spectrometry(ICP-OES). Additionally, pH Redox Equilibrium and C (PHREEQC),a geochemical model written in C programming language was employed to determine the saturation indices of mineral facies and ArcGIS 10.3.1 was used for spatial distribution patterns of IWQI. Then, the HHRA of nitrates and heavy metals was performed using United States environmental protection agency (USEPA)guidelines. The noteworthy outcomes include elevated levels of Ca2+, Mg2+, Cl-, NO3-, Cu,Fe, Mn, and Pb, demonstrating rock-water interaction, silicate weathering, Ca-Mg-HCO3 followed by mixed water facies, dissolution/precipitation, reverse exchange, and anthropogenic contamination are the major controlling processes in groundwater of southern Tirupati, India. The modified IWQI reveals that most groundwater samples (38%) fall under the bad quality class, with (47%) in the poor quality class and only (15%) classified as medium qualityclass in pre- and post-monsoon seasons. Elevated IWQI were observed in all directions except in the east, which is suitable for drinking. Moreover, the major hazard quotient (HQ) and hazard index (HI)for nitrates (NO3-) and heavy metals like copper(Cu), iron (Fe), manganese (Mn), lead (Pb) and zinc (Zn) are above the critical value of 1, revealing potential risk to humans, especially infants, followed by children and adults, entailing the instantaneous implementation of proper remedial measures and stringent policies to reduce the risk associated with groundwater pollution in the southern parts of Tirupati.

Hydrogeochemical appraisal, sources, quality and potential health risk assessment in Holocene and Pleistocene aquifers in Bangladesh.

This study integrated hydrochemical analysis, isotopic analysis, the integrated water quality index (IWQI), and the health risk assessment model to analyze hydrochemical characteristics, quality, and nitrate health risks in a typical agricultural and industrial (i.e., Holocene and Pleistocene) simultaneously affected byanthropogenic activities, as well as to explore the recharge mechanisms of the groundwater. The shallow groundwater is mainly Ca-HCO3- and deep groundwater is mainly Na-HCO3- types. In shallow and intermediate aquifers (Holocene), rainfall recharge is seen, but in deep aquifers (Holocene) and the Madhupur tract (Pleistocene), there is no evidence of recent recharge from the stable isotopic (δ2H‰ and δ18O‰) composition of groundwater. Anthropogenic sources significantly impacted the groundwater chemistry of shallow and intermediate aquifers more than geogenic sources. Most metalloids, and metals (As, and Cr, Fe, Ni, Pb, and Mn) and NO3- exceed the WHO-2011 and BD acceptable limit from shallow and intermediate groundwater. PCA analysis revealed the contamination of shallow and intermediate aquifers by metalloids, metals and from various anthropogenic activities. Based on the IWQI, HPI, HEI, and DC, groundwater samples from shallow and intermediate aquifers are unsuitable for oral consumption. The NPI shows that the metalloids, and metals are responsible for groundwater pollution in a descending order of As > Fe > Pb > Ni > Cr > Mn. Health risk assessment indicates oral and dermal consumption of contaminated water from shallow and intermediate aquifers can pose carcinogenic and non-carcinogenic health risks for both the adults and the children. The HQ and HI values of shallow and intermediate groundwater indicates higher non-carcinogenic risk. Carcinogenic risk through oral and dermal consumption follows an order of As > Ni > Cr > Pb and Ni > Cr > As > Pb, respectively. Compared to adults, children are more susceptible to both carcinogenic and non-carcinogenic risks. Potential threats to the health of people living in the study region need immediate attention from the public, government, and the scientific community.

Sensitivity analysis-driven machine learning approach for groundwater quality prediction: Insights from integrating ENTROPY and CRITIC methods

Precise estimation of water quality is essential for managing water pollution effectively and improving water management practices. Although, numerous recent investigations have documented inconsistencies in conventional water quality indexing methods owing to inherent subjective nature of its computation. Therefore, this study introduced a novel approach that integrates ENTROPY and CRITIC methods and applied sensitivity analysis-driven machine learning (ML) algorithms for groundwater quality prediction. The aim was to enhance prediction accuracy and robustness while gaining valuable insights into hydrochemical processes influencing groundwater quality. Six ML models, i.e., Support Vector Machine (SVM), Artificial Neural Network (ANN), Linear Regression Model (LRM), Regression Tree (RT), Gaussian Process Regression (GPR), and Boosted Regression Tree (BRT) were applied to forecast water quality across Tamil Nadu, India. This study addresses a significant gap, as systematic ML framework has been lacked to evaluate and predict drinking water quality across the same state, covering 619 monitoring sites. Calibration of the proposed Integrated Water Quality Index (IWQI) models was conducted using 75 % of the dataset (465 training wells) and validated with 25 % (154 monitoring wells), considering 13 physicochemical parameters. Rigorous statistical evaluations employing metrics such as RMSE, MSE, and MAE were performed to identify most effective prediction model, accounting for both uncertainty and predictive performance. This study suggest that ANN model is the most suitable, exhibiting the lowest uncertainty with R2 = 1 and the best predictive performance statistics, including RMSE (training = 0.0264, testing = 0.5638), MSE (training = 0.0007, testing = 0.3179), and MAE (training = 0.0083, testing = 0.0729). Sensitivity analysis identified electrical conductivity (EC) as highest responsive input parameter, while fluoride (F−) showed the lowest sensitivity. The robustness of the ANN model was evident, maintaining accuracy even with perturbations up to 10 %, thereby enabling precise IWQI score forecasting across all monitoring stations.

Assessment of coastal river water quality in Bangladesh: Implications for drinking and irrigation purposes.

Saltwater intrusion in the coastal areas of Bangladesh is a prevalent phenomenon. However, it is not conducive to activities such as irrigation, navigation, fish spawning and shelter, and industrial usage. The present study analyzed 45 water samples collected from 15 locations in coastal areas during three seasons: monsoon, pre-monsoon, and post-monsoon. The aim was to comprehend the seasonal variation in physicochemical parameters, including water temperature, pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), hardness, and concentrations of Na+, K+, Mg2+, Ca2+, Fe2+, HCO3-, PO43-, SO42-, and Cl-. Additionally, parameters essential for agriculture, such as soluble sodium percentage (SSP), sodium absorption ratio (SAR), magnesium absorption ratio (MAR), residual sodium carbonate (RSC), Kelly's ratio (KR), and permeability index (PI), were examined. Their respective values were found to be 63%, 16.83 mg/L, 34.92 mg/L, 145.44 mg/L, 1.28 mg/L, and 89.29%. The integrated water quality index was determined using entropy theory and principal component analysis (PCA). The resulting entropy water quality index (EWQI) and SAR of 49.56% and 63%, respectively, indicated that the samples are suitable for drinking but unsuitable for irrigation. These findings can assist policymakers in implementing the Bangladesh Deltaplan-2100, focusing on sustainable land management, fish cultivation, agricultural production, environmental preservation, water resource management, and environmental protection in the deltaic areas of Bangladesh. This research contributes to a deeper understanding of seasonal variations in the hydrochemistry and water quality of coastal rivers, aiding in the comprehension of salinity intrusion origins, mechanisms, and causes.

Groundwater quality characterization using an integrated water quality index and multivariate statistical techniques.

This study attempts to characterize and interpret the groundwater quality (GWQ) using a GIS environment and multivariate statistical approach (MSA) for the Jakham River Basin (JRB) in Southern Rajasthan. In this paper, analysis of various statistical indicators such as the Water Quality Index (WQI) and multivariate statistical methods, i.e., principal component analysis and correspondence analysis (PCA and CA), were implemented on the pre and post-monsoon water quality datasets. All these methods help identify the most critical factor in controlling GWQ for potable water. In pre-monsoon (PRM) and post-monsoon (POM) seasons, the computed value of WQI has ranged between 28.28 to 116.74 and from 29.49 to 111.98, respectively. As per the GIS-based WQI findings, 63.42 percent of the groundwater samples during the PRM season and 42.02 percent during the POM were classed as 'good' and could be consumed for drinking. The Principal component analysis (PCA) is a suitable tool for simplification of the evaluation process in water quality analysis. The PCA correlation matrix defines the relation among the water quality parameters, which helps to detect the natural or anthropogenic influence on sub-surface water. The finding of PCA's factor analysis shows the impact of geological and human intervention, as increased levels of EC, TDS, Na+, Cl-, HCO3-, F-, and SO42- on potable water. In this study, hierarchical cluster analysis (HCA) was used to categories the WQ parameters for PRM and POR seasons using the Ward technique. The research outcomes of this study can be used as baseline data for GWQ development activities and protect human health from water-borne diseases in the southern region of Rajasthan.

Novo Índice Integrado de Qualidade da Água (IWQI) e sua aplicação com poluentes emergentes na bacia do bioma Mata Atlântica no sul do Brasil

ABSTRACT The presence of emerging contaminants in surface water is a growing concern, as these substances are not typically monitored by environmental quality systems, potentially leading to the consumption of contaminated water. In this study, the presence of caffeine, an emerging contaminant that is ingested solely by humans and is present in surface water due to its chemical characteristics, was investigated as a potential indicator of anthropogenic contamination in the Itajaí-Açu River in the southern Brazilian Atlantic Forest biome. Additionally, twelve other emerging pollutants were examined in the Itajaí-Açu River, including estrone (E1), estradiol (E2), ethinylestradiol (EE2), estriol (E3), prednisone (PD), hexestrol (HEX), acetaminophen (ACM), Oxytetracicline (OC). Surface water samples were collected over five months and analyzed using high-performance liquid chromatography. The results revealed that caffeine was present in 84% of the analyzed samples, and emerging pollutants were present in all monitored municipalities. The study also investigated the relationship between an integrated water quality index, the magnitudes and occurrences of caffeine, and land use. The emerging pollutants Estrone, Ethinylestradiol, Hexestrol, Naproxen and Oxytetracycline were not detected in the analyzed samples. However, Ibuprofen, Tetracycline, Prednisone, and Acetaminophen were present in 44% and 36% of the samples, respectively, with Estriol, Ketoprofen, and Estradiol having a lower occurrence. The mean concentrations of Estradiol, Estriol, Ketoprofen, Acetaminophen, and Ibuprofen were 0.08 µg L-1, 0.23 µg L-1, 0.15 µg L-1, 0.42 µg L-1, and 0.44 µg L-1, respectively, and were higher than previously reported. The concentration range of caffeine during the study was <0.10 to 1.48 µg L-1, with the mean concentration being 0.30 µg L-1. These findings highlight the presence of emerging pollutants in the Itajaí-Açu River and the need for continued monitoring and regulatory legislation to protect surface water quality in Brazil.

GIS-BASED LANDSCAPE MANAGEMENT OF THE UZH RIVER BASIN: A STRATEGY TO ENHANCE RIVER WATER QUALITY

The article includes the findings of a study on the Uzh River basin’s surface water’s quality. This region is extremely important because a fraction of it is radioactively contaminated because of the Chornobyl nuclear power plant accident. Considering this, the goal of this work was to conduct a geo-informational analysis of the state and structure of the landscapes of the Uzh River basin, to identify the surface water quality parameters of this region, and to identify potential correlations between these parameters. For this purpose, we spatially divided the territory of the basin into separate massifs, in each of which, using the method of automatic decoding, we determined the ratio of the structural components of landscapes, their disturbance by erosion processes, and compared them with ground data on the quality of surface water of the massifs. According to the salt composition, all the investigated massifs have good quality conditions. The Uzh River and its tributaries should be categorized as 4 (slightly polluted) based on the average values of the trophosaprobological state, but the extreme values in some places shifted to 5 (moderately polluted). Most of the listed toxic substances were present at average levels and, for the most part, did not exceed the permitted concentrations for category 4-slightly polluted. Extreme concentrations frequently reached category 6 (polluted), which was primarily brought on by anthropogenic activity and the buildup of radioactive materials. It was found that the degree of erosive landscape destruction and the degree of landscape stabilization significantly influence the value of the integrated water quality index. Since the collected data, a three-dimensional model was developed, allowing for accurate evaluations and projections of changes in the quality of surface water based on the structural characteristics of the land shafts. Considering that some of these territories are currently in the zone of radioactive contamination, the planning of changes in the landscape structure should be coordinated with the potential risks of surface water quality deterioration, and the model proposed in this article will have significant applied value in addressing this issue.

Evaluation of groundwater in aluminium slag disposal area

Aluminium slag waste is a residue from aluminium recycling activities, classified as hazardous waste so its disposal into the environment without processing can cause environmental problems, including groundwater pollution. There are 90 illegal dumping areas for aluminium slag waste spread in the Sumobito District, Jombang Regency. This study aims to evaluate the quality of shallow groundwater surrounding aluminium slag disposal in the Sumobito District for drinking water. The methods applied an integrated water quality index ( WQI) and heavy metal pollution index ( HPI), multivariate analysis (principal component analysis (PCA) and hierarchical clustering analysis (HCA)), and geospatial analysis for assessing groundwater quality. The field campaign conducted 40 groundwater samples of the dug wells for measuring the groundwater level and 30 of them were analysed for the chemical contents. The results showed that some locations exceeded the quality standards for total dissolved solids ( TDS), electrical conductivity (EC), and Al 2+. The WQI shows that 7% of dug well samples are in poor drinking water condition, 73% are in good condition, and 20% are in excellent condition. The level of heavy metal contamination based on HPI is below the standard limit, but 13.3% of the water samples are classified as high contamination. The multivariate analysis shows that anthropogenic factors and natural sources/geogenic factors contributed to shallow groundwater quality in the study area. The geospatial map shows that the distribution of poor groundwater quality is in the northern area, following the direction of groundwater flow, and is a downstream area of aluminium slag waste contaminants.

Long-Term Water Quality Prediction Using Integrated Water Quality Indices and Advanced Deep Learning Models: A Case Study of Chaohu Lake, China, 2019–2022

The rapid development of urban industrialization has had many negative effects on the quality of water sources around cities. Long-term prediction of water quality can be of great help to the conservation of water environment. This case tries to use several popular deep learning models, such as RNN, LSTM, MLP, and Transformer-based models to predict the long-term integrated water quality index in the Chaohu Lake area. The dataset is derived from daily monitoring data from four monitoring sites within Chaohu Lake from 2019 to 2022, and the long-term prediction performance of the model is evaluated using MAE and MSE as evaluation metrics. The experimental results showed that all models selected in this case achieved good results within the study area, but Informer performed more prominently (MSE = 0.2455, MAE = 0.2449) as the length of the prediction series increased. Our results demonstrate the effectiveness of popular deep learning models in the field of WQI prediction, especially the significant advantage of transformer-based models represented by Informer in long-term water quality prediction, which will further provide an effective modern tool for water quality monitoring and management.

A comprehensive water quality index based on analytical hierarchy process

The popular water quality index (WQI) and the recently developed integrated water quality index (IWQI) were used to evaluate the potability of 32 groundwater samples collected from Nalagarh valley, Himachal Pradesh, India. But their analytical results were surprisingly contrasting. While WQI classified 14 of the samples as ‘excellent’ and 17 as ‘good’, IWQI put all of them under ‘unsuitable’ category. This led to the development of a new index, called ‘comprehensive water quality index (CWQI)’, on the basis of analytical hierarchy process (AHP). Unit weights and sub-index values of both relaxable (that have both acceptable and permissible limits) and non-relaxable (that have only one guideline value) parameters were considered in the calculation process. Two segments were calculated: PCWQI (positive CWQI) and NCWQI (negative CWQI) with their scores varying between 0 and 1 and 0 and (−0.840), respectively. Grading of water quality from drinking perspective was done essentially with NCWQI scores, such as ‘excellent’ (when NCWQI = 0), ‘good’ (NCWQI = 0 to −0.21), ‘marginal’ (NCWQI = −0.21 to −0.42), ‘poor’ (NCWQI = −0.42 to −0.63), ‘very poor’ (NCWQI = −0.63 to −0.84) and ‘unacceptable’ (NCWQI = <−0.84). In fact, whenNCWQI = 0, higher the PCWQI, better the water quality. When two water samples had the same NCWQI score, they were graded by their respective PCWQI score. When two water samples had the same magnitudes of PCWQI and NCWQI, they were graded equally. On the basis of this classification, groundwater in majority of the study area was classified under ‘good’ category for drinking purposes in absence of an alternative source of water. Compared to WQI and IWQI, CWQI proved itself to be a robust and comprehensive technique for assessing the groundwater quality. It was hence recommended to be used universally for groundwater quality assessment.

Evaluation of hydrochemistry and identification of pollution hotspots of little Akaki river using integrated water quality index and GIS

Despite unwavering effort of the government, urban river pollution in Ethiopia has remained a worrisome phenomenon now a days. This research is conducted with a prime aim of assessing and evaluating the water quality status and identifying and mapping of the pollution hotspots in the Little Akaki River (LAR), Ethiopia by integrating the water quality index (CCME-WQI) and Geographic Information System (GIS). Accordingly, water quality samples were collected from 22 monitoring stations. The water samples were collected and analyzed for physico-chemical and heavy metal constituents using the American Public Health Association (APHA) standard methods. Most of the physico-chemical constituents analyzed have surpassed the standard guideline value of the country and World Health Organization (WHO). In addition, most of the middle (S3-S10) segments of the river is heavily polluted than the downstream segment (S11-S14) and upstream segments. Similarly, the heavy metals concentrations in the LAR have decreasing trend with Mn>Zn>Pb>Cu>Cd. On the other hand, the overall CCME-WQI modeling output ranged from 18.9 – 36.2. Accordingly, the finding of the study reveals that most water quality parameters were beyond ambient surface water quality standards and the CCME-WQI categorizes all the monitoring stations under poor water quality state. Besides, the spatial distribution of pollution in LAR shows intense deterioration at the middle segment of the river and needs a proper strategic management plan in the catchment and immediate protection and restoration of the natural ecology of the LAR. It is recommended to integrate river water pollution management and maintain ecologically to achieve healthy urban development.

Development of modified integrated water quality index to assess the surface water quality: a case study of Tuo River, China.

Water quality evaluation is an important step in water environment control and management. The water quality index (WQI) is considered to be an effective method for water quality evaluation. However, when constructing the WQI, the contribution of the lower threshold limits of water quality parameters to water quality has received little attention. The principle of the modified integrated water quality index (IWQI) is that the concentration of any water quality parameter below the lower threshold limits as well as above the upper threshold limits will lead to an increase in the overall index value. Based on the concentration of water quality parameters, the modified IWQI classified water quality into five categories, i.e., bad (> 8), poor (5-8), medium (2-5), good (1-2), and excellent (< 1). Tuo River plays a crucial role in potable and irrigation water sources of Sichuan Province, and the assessment result of modified IWQI reveals that 67.8% of samples were classified as "medium," 29% "poor," and 3.2% "bad." The high concentrations of N and P from agricultural activities and industrial wastewater are the main contributors to the deterioration of water quality in the Tuo River. Additionally, the Tuo River presents the characteristics of worse water quality in the midstream. The evaluation results of the modified IWQI are consistent with that of the conventional WQI, which proves the accuracy of the modified IWQI as a surface water quality evaluation method.

Evaluation of groundwater quality of Prayagraj city using entropy water quality index (EWQI) and new integrated water quality index (IWQI)

Evaluation of groundwater quality of Prayagraj city using entropy water quality index (EWQI) and new integrated water quality index (IWQI)

Assessment of potability of minewater pumped out from Jharia Coalfield, India: an integrated approach using integrated water quality index, heavy metal pollution index, and multivariate statistics.

The dense and industrialized populace in the mining areas of Jharia Coalfield (JCF) is plagued by a severe shortage of water supply. The unutilized pumped out coal minewater discharges may be utilized to cater to the increasing water demand of the region but it runs the risk of getting contaminated from domestic and industrial effluents. The current study aimed to assess the suitability of augmenting underground minewater for potable purposes. For this purpose, ninety underground minewater samples collected from 15 locations across JCF for the hydrological year 2019-2020 were analysed to gain an insight on the physicochemical characteristics of the minewater using an integrated approach of standard hydrochemical methods, integrated water quality index (IWQI), heavy metal pollution index (HPI), and multivariate statistical analysis. For the minewater quality to be deemed suitable for potable purposes, both IWQI (lower than 2) and HPI (lower than 30) values were considered. IWQI values of the minewater samples from the study area ranged from 1.97 to 5.08, while the HPI values ranged from 18.40 to 53.05. The pH of the samples were found to be mildly acidic to alkaline (6.5 to 8.3) with varying total hardness (149 to 719mg L-1), total dissolved solids (341 to 953mg L-1), and electrical conductivity (568 to 1389 µS cm-1), reflecting heterogeneity in underlying hydrosystems, variations in geological formations, and the influence of lithogenic and anthropogenic processes on the water chemistry of the region, which was corroborated by the principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the minewater samples. Two major water types of the region were identified, viz., Ca-Mg-HCO3 and Ca-Mg-Cl-SO4. This multiparametric approach gives a holistically accurate assessment of the minewater quality, overcoming the limitations of traditional water quality indices and facilitating time-saving and effective water management practices, and sets the foundation for augmenting minewater for potable purposes to meet increasing demands.

Geospatial distribution of groundwater quality using entropy water quality index and statistical assessment: A study from a tropical climate river basin

AbstractA combination of multivariate statistical techniques and an integrated water quality index methodology was adopted to understand the genesis of major ionic composition of groundwater in a tropical river basin of South India. The present study aims to examine the hydrochemical characterisation and drinking suitability of groundwater reserves of Kallada River Basin (KRB), India by collecting samples from 31 wells during pre‐monsoon (May 2019), monsoon (September 2019), and post‐monsoon (February 2020) seasons. The findings were compared with the maximum acceptable limites prescribed by Bureau of Indian Standards (BIS 2012) and World Health Organization (WHO 2017). The study also highlights the comparison of the present work with the regional and global average cation and anion concentrations. The Principal Component Analysis (PCA) extracted three factors and the obtained results shows that Cl−, TDS, Na+, and Ca2+ ions contribute towards the moderate pollution load in groundwater. The increased population around the river basin indicates the unhygienic practices in the area and hence eco‐friendly authority steps/actions should be taken to enhance the groundwater quality of the basin. The findings of this study outlines the desire for groundwater research with a further marked focus on upgrading the quantity and quality of groundwater reserves on a global scale.

Evaluation of Groundwater Using an Integrated Approach of Entropy Weight and Stochastic Simulation: A Case Study in East Region of Beijing.

Groundwater is an important source of water in Beijing. Hydrochemical composition and water quality are the key factors to determine the availability of groundwater. Therefore, an improved integrated weight water quality index approach (IWQI) combining the entropy weight method and the stochastic simulation method is proposed. Through systematic investigation of groundwater chemical composition in different periods, using a hydrogeochemical diagram, multivariate statistics and spatial interpolation analysis, the spatial evolution characteristics and genetic mechanism of groundwater chemistry are discussed. The results show that the groundwater in the study area is weakly alkaline and low mineralized water. The south part of the study area showed higher concentrations of total dissolved solids, total hardness and -N in the dry season and wet season, and the main hydrochemical types are -Ca and -Ca-Mg. The natural source mechanism of the groundwater chemical components in Chaoyang District includes rock weathering, dissolution and cation exchange, while the human-made sources are mainly residents and industrial activities. Improved IWQI evaluation results indicate that water quality decreases from southwest to northeast along groundwater flow path. The water quality index (WQI) method cannot reflect the trend of groundwater. Sensitivity analysis indicated that the improved IWQI method could describe the overall water quality reliably, accurately and stably.

Surface water quality assessment based on the Integrated Water Quality Index in the Maozhou River basin, Guangdong, China

Rivers are a vital component of both urban and rural aquatic ecosystems, and the rapidly increasing pollution in rivers severely threatens the security of these ecosystems. In this study, the surface water quality in the Maozhou River basin, Guangdong Province, China, was assessed from 2018 to 2020 using multivariate statistical techniques and the Integrated Water Quality Index (IWQI). In addition, spatial trends in surface water quality were studied using a geographic information system. The results indicated that the water quality in 82.17% of the studied section met the Class V standard for surface water quality, with IWQI values ranging from 12.157 to 3.650. The surface water quality was clustered into eight groups and further divided into unsuitable (low quality) and suitable (acceptable quality) according to standard surface water quality thresholds (China in Environmental quality standards for surface water, 2002). Four groups (G1, G2, G3, and G4) were classified as unsuitable, because they fell short of the Class V standard for surface water quality. In these groups, industrial sewage, endogenous pollution, domestic sewage, and rainfall runoff, were the primary sources of pollution, and the main background pollutants for the water quality target of the functional zones were COD, NH3-N, TP, and LAS. The other four groups were classified as suitable. In these groups, endogenous pollution and rainfall runoff were the primary sources of pollution, and the main background pollutants for the water quality target of the functional zones were NH3-N and TP. Among them, NH3-N and LAS were recognized as responsive and sensitive to the surface water quality and spatio-temporal variability. Owing to pollution treatment and management measures undertaken by the Chinese government, the black-odorous water in the Maozhou River basin has disappeared, and the water quality in the Maozhou River basin has been maintained at the “medium and good” level. However, the surface water quality in the estuary region and the southwest tributary in the basin requires further improvement. This calls for further efforts to improve surface water quality and to properly deal with various sources of pollution in the watershed. This combined method has proved to be effective for surface water quality evaluation and management at river or basin scales. The results of this work are expected to provide a scientific foundation for aquatic ecosystem management and planning.

Impacts and social implications of landuse-environment conflicts in a typical Mediterranean watershed

In coastal watersheds, services and landuse favour coastal tourism and urbanization, depriving rural upstream of infrastructure and attention. This unbalanced management leads to an intensification of socioeconomic changes that generate a structural heterogeneity of the landscape and a reduction in the livelihoods of the rural population. The incessant dissociation between the objectives of the stakeholders triggers landuse-environment-economy conflicts which threaten to mutate large-scale development programs. Here, we used multi-assessment techniques in a Mediterranean watershed from Morocco to evaluate the effects of landuse change on water, vegetation, and perception of the rural population towards environmental issues. We combined complementary vegetation indexes (NDVI and EVI) to study long-term landuse change and phenological statistical pixel-based trends. We assessed the exposure of rural households to the risk of groundwater pollution through a water analysis supplemented by the calculation of an Integrated Water Quality Index. Later, we contrasted the findings with the results of a social survey with a representative sample of 401 households from 7 villages. We found that rapid coastal linear urbanization has resulted in a 12-fold increase in construction over the past 35 years, to the detriment of natural spaces and the lack of equipment and means in rural areas upstream. We show that the worst water qualities are linked to the negative impact of anthropogenic activities on immediately accessible water points. We observe that rural households are aware of the existence and gravity of environmental issues but act confusedly because of their low education level which generates a weak capacity to understand cause and effect relationships. We anticipate the pressing need to improve the well-being and education of the population and synergistically correct management plans to target the watershed as a consolidated system. Broadly, stakeholders should restore lost territorial harmony and reallocate landuse according to a sustainable environment-socioeconomic vision.