Qualidex--a new software for generating water quality indices

Spatiotemporal pattern of coastal water pollution and its driving factors: implications for improving water environment along Hainan Island, China

In the context of human activities and climate change, the gradual degradation of coastal water quality seriously threatens the balance of coastal and marine ecosystems. However, the spatiotemporal patterns of coastal water quality and its driving factors were still not well understood. Based on 31 water quality parameters from 2015 to 2020, a new approach of optimizing water quality index (WQI) model was proposed to quantitatively assess the spatial and temporal water quality along tropical Hainan Island, China. In addition, pollution sources were further identified by factor analysis and the effects of pollution source on water quality was finally quantitatively in our study. The results showed that the average water quality was moderate. Water quality at 86.36% of the monitoring stations was good while 13.53% of the monitoring stations has bad or very bad water quality. Besides, the coastal water quality had spatial and seasonal variation, along Hainan Island, China. The water quality at "bad" level was mainly appeared in the coastal waters along large cities (Haikou and Sanya) and some aquaculture regions. Seasonally, the average water quality in March, October and November was worse than in other months. Factor analysis revealed that water quality in this region was mostly affected by urbanization, planting and breeding factor, industrial factor, and they played the different role in different coastal zones. Waters at 10.23% of monitoring stations were at the greatest risk of deterioration due to severe pressure from environmental factors. Our study has significant important references for improving water quality and managing coastal water environment.

Spatio-temporal evolution of eutrophication and water quality in the Turawa dam reservoir, Poland

The objectives of the article are: to assess spatio-temporal evolution of eutrophication and water quality of the Turawa dam reservoir, located in south-western Poland on the Mała Panew River; to identify location and relationship between potential sources of physicochemical pollution related to the progressing process of eutrophication; and to determine trophic status and water quality indices of the selected research object. The analysis (Mann-Whitney U test, PCA, HCA, Spearman correlation matrix) showed a high susceptibility of the reservoir to eutrophication processes, especially due to the influence of dangerous loads of compounds emerging from areas with high tourist intensity and pollutants flowing from the Mała Panew River. The parameters deteriorating the ecological status were TP, DO, BOD₅, and COD. Considering the cumulative results of water quality indices for the period 1998-2020, the average water quality was in classes II or III. A noticeable deterioration appeared in water quality for the years 2016-2020, which proves the progressing eutrophication in the Turawa reservoir. In 1998-2020, the reservoir was classified as eutrophic or mesoeutrophic based on the calculated three trophic status indices. This article would help in developing a strategy for dealing with water blooms, a reliable system for monitoring pressures causing eutrophication, and optimal technologies for the reconstruction of multifunctional reservoirs.

Assessing water quality in the Dong Nai River (Vietnam): implications for sustainable management and pollution control

Dong Nai River provides essential water resources for millions of people across 11 provinces and cities in Vietnam. However, the different pollution sources such as household, farming, and industrial operations have caused the river water quality to deteriorate over the past decade. To gain a comprehensive understanding of the river's surface water quality, this study employed the water quality index (WQI) across 12 different sampling sites. In total,144 water samples with 11 parameters were analyzed in accordance with the Vietnamese standard 08:2015/MONRE. Results revealed a range of surface water quality, from poor to good according to the VN-WQI (Vietnamese standard), and a medium even bad level in some months according to the NS-WQI (American standard). The study also identified temperature, coliform, and dissolved oxygen (DO) as strong contributors to WQI values (VN_WQI standard). Principal component analysis/factor analysis was used to determine pollution sources, with the results highlighting agricultural and domestic activities as the main contributors to river pollution. In conclusion, this study underscores the importance of effective planning and management of infrastructure zoning and local activities to improve the river's surface water quality and surrounding areas, as well as safeguard the well-being of the millions who depend on it.

A systematic and comparative study of Water Quality Index (WQI) for groundwater quality analysis and assessment

Water is essential for human survival. Its quality must be maintained to prevent any potential health problems. Pollution and contamination are likely causes of the water quality decline. This may occur if the world's rapidly expanding population and industrial facilities fail to clean their effluent correctly. The Water Quality Index, often known as the WQI, is the indicator most frequently used to characterize surface water quality. This study emphasizes several WQI models that could be of use to us in determining the level of water quality available in the various areas. We have tried to cover multiple essential procedures and their corresponding mathematical counterparts. In this article, we also examine the applications of index models in different types of water bodies, such as lakes, rivers, surface water, and groundwater. The level of contamination in water due to pollution directly affects the overall quality of water. A pollution index is a valuable tool for measuring the level of pollution. Concerning this, we have discussed two approaches, namely, the Overall Index of Pollution and Nemerrow's Pollution Index, which demonstrate the most effective technique to evaluate the water standard. Examining the similarities and differences between these approaches may offer researchers a suitable starting point to delve further into assessing water quality.

Revised Iranian Water Quality Index (RIWQI): a tool for the assessment and management of water quality in Iran

Water quality indices use biological, chemical, and physical data and information to classify the condition of surface waters, ultimately contributing to their management. We used multicollinearity and principal components analyses to develop the Revised Iranian Water Quality Index (RIWQI) as an indicator of agricultural and urban effects in the Karun River Basin of southwestern Iran. Seasonal sampling and analysis of water quality parameters from 54 sites across 18 rivers of the Karun River Basin include fecal coliform, total dissolved solid, phosphate, biological and chemical oxygen demand, nitrate, dissolved oxygen saturation, turbidity, pH, and water temperature. This study updates the previous version of Iranian Water Quality Index (IWQI) by differentially weighting individual variables, refining the main sub-indices, adding phosphate (PO₄^-), biological oxygen demand (BOD), chemical oxygen demand (COD), and temperature (T), and improving the aggregation calculation. Sensitivity testing of the RIWQI resulted in a mean value for discrimination efficiency (DE) > 85.6%, the highest of other indices calculated with the same dataset.

Impact of a small hydropower plant on water quality dynamics in a diversion and natural river channel

This study innovatively evaluates the impact of hydropower plants located in a diversion channel on water quality dynamics. The spatial characteristics of water in the diversion channel above and below a hydropower plant were assessed; specifically, the investigation was conducted in the watercourse undeveloped by the hydropower plant and at reference points. Among the five analyzed points, the strongest statistically significant changes were observed in electrical conductivity, pH, and dissolved oxygen. Statistical analyses showed a similar, statistically significant relationship for most months. The water quality indicators proposed in this study help assess hydropower plants' impact on water quality dynamics because they enable water comparison at different locations. The best water quality, as calculated using designated indices, was recorded below the hydropower plant. Among the physicochemical parameter values, the most noticeable change occurred in dissolved oxygen below the hydropower plant and below the fixed weir; its value was 8.10 and 5.32% higher in the two locations at the reference point below the hydropower facility. Moreover, the NH₄ -N content was higher by 7.06% below the weir than the point below the hydropower plant. In the long term, this research may help plant operators manage water resources on watercourses with hydropower development more efficiently, according to sustainable development principles. This research will contribute to the rational management of such facilities on diversion channels considering sustainable water management principles.

Assessing the Water Quality of Lake Hawassa Ethiopia-Trophic State and Suitability for Anthropogenic Uses-Applying Common Water Quality Indices

The rapid growth of urbanization, industrialization and poor wastewater management practices have led to an intense water quality impediment in Lake Hawassa Watershed. This study has intended to engage the different water quality indices to categorize the suitability of the water quality of Lake Hawassa Watershed for anthropogenic uses and identify the trophic state of Lake Hawassa. Analysis of physicochemical water quality parameters at selected sites and periods was conducted throughout May 2020 to January 2021 to assess the present status of the Lake Watershed. In total, 19 monitoring sites and 21 physicochemical parameters were selected and analyzed in a laboratory. The Canadian council of ministries of the environment (CCME WQI) and weighted arithmetic (WA WQI) water quality indices have been used to cluster the water quality of Lake Hawassa Watershed and the Carlson trophic state index (TSI) has been employed to identify the trophic state of Lake Hawassa. The water quality is generally categorized as unsuitable for drinking, aquatic life and recreational purposes and it is excellent to unsuitable for irrigation depending on the sampling location and the applied indices. Specifically, in WA WQI, rivers were excellent for agricultural uses and Lake Hawassa was good for agricultural uses. However, the CCME WQI findings showed rivers were good for irrigation but lake Hawassa was marginal for agricultural use. Point sources were impaired for all envisioned purposes. The overall category of Lake Hawassa falls under a eutrophic state since the average TSI was 65.4 and the lake is phosphorous-deficient, having TN:TP of 31.1. The monitored point sources indicate that the city of Hawassa and its numerous industrial discharges are key polluters, requiring a fast and consequent set-up of an efficient wastewater infrastructure, accompanied by a rigorous monitoring of large point sources (e.g., industry, hospitals and hotels). In spite of the various efforts, the recovery of Lake Hawassa may take a long time as it is hydrologically closed. Therefore, to ensure safe drinking water supply, a central supply system according to World Health organization (WHO) standards also for the fringe inhabitants still using lake water is imperative. Introducing riparian buffer zones of vegetation and grasses can support the direct pollution alleviation measures and is helpful to reduce the dispersed pollution coming from the population using latrines. Additionally, integrating aeration systems like pumping atmospheric air into the bottom of the lake using solar energy panels or diffusers are effective mitigation measures that will improve the water quality of the lake. In parallel, the implementation and efficiency control of measures requires coordinated environmental monitoring with dedicated development targets.

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Human activities continue to affect our water quality; it remains a major problem worldwide (particularly concerning freshwater and human consumption). A critical water quality index (WQI) method has been used to determine the overall water quality status of surface water and groundwater systems globally since the 1960s. WQI follows four steps: parameter selection, sub-indices, establishing weights, and final index aggregation, which are addressed in this review. However, the WQI method is a prolonged process and applied to specific water quality parameters, i.e., water consumption (particular area and time) and other purposes. Therefore, this review discusses the WQI method in simple steps, for water quality assessment, based on two multi-criteria decision-making (MCDM) methods: (1) analytical hierarchical process (AHP); and (2) measuring attractiveness by a categorically based evaluation technique (MACBETH). MCDM methods can facilitate easy calculations, with less effort and great accuracy. Moreover, the uncertainty and eclipsing problems are also discussed—a challenge at every step of WQI development, particularly for parameter selection and establishing weights. This review will help provide water management authorities with useful knowledge pertaining to water usage or modification of existing indicators globally, and contribute to future WQI planning and studies for drinking, irrigation, domestic, and industrial purposes.

Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index

In recent decades, various conventional techniques have been formulated around the world to evaluate the overall water quality (WQ) at particular locations. In the present study, back propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), and one multilinear regression (MLR) are considered for the prediction of water quality index (WQI) at three stations, namely Nizamuddin, Palla, and Udi (Chambal), across the Yamuna River, India. The nonlinear ensemble technique was proposed using the neural network ensemble (NNE) approach to improve the performance accuracy of the single models. The observed WQ parameters were provided by the Central Pollution Control Board (CPCB) including dissolved oxygen (DO), pH, biological oxygen demand (BOD), ammonia (NH₃), temperature (T), and WQI. The performance of the models was evaluated by various statistical indices. The obtained results indicated the feasibility of the developed data intelligence models for predicting the WQI at the three stations with the superior modelling results of the NNE. The results also showed that the minimum values for root mean square (RMS) varied between 0.1213 and 0.4107, 0.003 and 0.0367, and 0.002 and 0.0272 for Nizamuddin, Palla, and Udi (Chambal), respectively. ANFIS-M3, BPNN-M4, and BPNN-M3 improved the performance with regard to an absolute error by 41%, 4%, and 3%, over other models for Nizamuddin, Palla, and Udi (Chambal) stations, respectively. The predictive comparison demonstrated that NNE proved to be effective and can therefore serve as a reliable prediction approach. The inferences of this paper would be of interest to policymakers in terms of WQ for establishing sustainable management strategies of water resources.

Water Quality Index of Suceava River in Suceava City Metropolitan Area

The water quality of rivers worldwide is of persistent interest due to its impact on human life. Five streamwater quality parameters of Suceava River were monitored in 2019 upstream and downstream of Suceava city, Romania: dissolved oxygen, specific conductivity, pH, oxidation-reduction potential, and temperature. Data was recorded at a high temporal frequency, every hour, and produced Water Quality Index (WQI) time series of similar resolution. Our additive WQI has variants with particular advantages. Water quality of Suceava city exhibits a diurnal cycle. Upstream, WQI values indicate a quasi-permanent good water quality; downstream, the water quality oscillates around the average WQI value because of the various sources of water contaminants, especially the wastewaters from the wastewater treatment plant. Parameters from this point source of pollution are taken into account to explain the decaying streamwater quality towards the end of 2019. WQI is useful for detecting time intervals when water self-purification events have a high chance of occurrence.

Assessment of the water quality of a subtropical lake using the NSF-WQI and a newly proposed ecosystem specific water quality index

A Water Quality Index (WQI) is a formulation that enables the estimation of the overall quality of a water body based on significant parameters. One example of this is the well-known and widely accepted NSF-WQI, which is frequently used to assess chemical, physical, and microbiologic features of waterbodies in temperate latitudes. In this work, a well-structured method, completely based on multivariate statistical methods and historical data distributions, was used to develop an ecosystem specific water quality index (ES-WQI). Lake Cajititlán, a subtropical Mexican lake located in Tlajomulco de Zúñiga, was selected as a case of study because it is an endorheic shallow lake that shows signs of high levels of eutrophication due to anthropogenic contamination. As a result of the contamination, and its sensibility to changes in the water level, it undergoes important changes in its water features, such as turbidity and intense green color, and experiences massive events of fish mortality. The proposed ES-WQI describes the changes in water quality over the year well and correlates with the capability of the lake to support aquatic life, as the lowest estimated values coincide with the biggest events of massive fish mortality in the lake. Furthermore, the ES-WQI clearly differentiates between typical cyclic behaviors and actual deteriorating trends and is capable of tracking incremental changes all over the range of the possible concentration values of the water quality parameters.

Allocation of weights using factor analysis for development of a novel water quality index

Water quality assessment and monitoring is one of the most important aspects for ensuring a good environmental health. A Water Quality Index (WQI) is one of the most frequently used tools for assessing overall quality of water resources. This study uses Factor Analysis (FA) for one of the most significant steps in WQI development - weight determination. Factor analysis has been applied to the water quality parameters shortlisted from Principal Component Analysis in the study area and it grouped the parameters into different sets of loadings. Each loading contained a group of parameters contributing to the overall variance addressed by that loading. Weights were allocated to each loading as well as to individual parameters within each loading. For final aggregation, a hybrid method was followed; where weighted harmonic means were estimated for the parameters within each loading and weighted arithmetic mean was estimated from the results of harmonic mean. The use of multivariate statistical technique reduces the subjectivity in the development of the final WQI and makes the current study a useful step in future for the development of a Ganga Water Quality Index (GWQI). In addition to this, the developed methodology can also be used for developing WQI for any water body depending on the availability of historical data.

Potential of joyweed Alternanthera sessilis for rapid treatment of domestic sewage in SHEFROL® bioreactor

In a first-ever report on this subject, it is shown that a common amphibious plant joyweed (Alternanthera sessilis) can be used in rapid and efficient treatment of biodegradable wastewaters, typified by domestic sewage. The plant was effective when used indoors under artificial lighting, as well as outdoors. It enabled treatment of sewage, varying widely in strength (from 300 mg/L to 1800 mg/L in chemical oxygen demand), to the extent of 78.9-83.9%. It was also able to remove biological oxygen demand, suspended solids, phosphorous, nitrogen, and the heavy metal copper to the extent of 87%, 93%, 45%, and 43%, respectively. Over 99% of total coliforms, faecal coliforms, and faecal streptococci were also removed. The treatment was very swiftly achieved, at a hydraulic retention time of just 6 h, in the "sheet flow root level" (SHEFROL^®) bioreactor developed earlier by us and of which a patent claim has been registered. The findings indicate that A. sessilis has the potential to affect primary, secondary, and tertiary treatment of domestic sewage along with significant pathogen removal in a single process step when used in SHEFROL^® bioreactors.

Assessing regulatory violations of disinfection by-products in water distribution networks using a non-compliance potential index

Inactivating pathogens is essential to eradicate waterborne diseases. However, disinfection forms undesirable disinfection by-products (DBPs) in the presence of natural organic matter. Many regulations and guidelines exist to limit DBP exposure for eliminating possible health impacts such as bladder cancer, reproductive effects, and child development effects. In this paper, an index named non-compliance potential (NCP) index is proposed to evaluate regulatory violations by DBPs. The index can serve to evaluate water quality in distribution networks using the Bayesian Belief Network (BBN). BBN is a graphical model to represent contributing variables and their probabilistic relationships. Total trihalomethanes (TTHM), haloacetic acids (HAA5), and free residual chlorine (FRC) are selected as the variables to predict the NCP index. A methodology has been proposed to implement the index using either monitored data, empirical model results (e.g., multiple linear regression), and disinfectant kinetics through EPANET simulations. The index's usefulness is demonstrated through two case studies on municipal distribution systems using both full-scale monitoring and modeled data. The proposed approach can be implemented for data-sparse conditions, making it especially useful for smaller municipal drinking water systems.

Development of river water quality indices-a review

The use of water quality indices (WQIs) as a tool to evaluate the status of water quality in rivers has been introduced since the 1960s. The WQI transforms selected water quality parameters into a dimensionless number so that changes in river water quality at any particular location and time could be presented in a simple and easily understandable manner. Although many WQIs have been developed, there is no worldwide accepted method for implementing the steps used for developing a WQI. Thus, there is a continuing interest to develop accurate WQIs that suit a local or regional area. This paper aimed to provide significant contribution to the development of future river WQIs through a review of 30 existing WQIs based on the four steps needed to develop a WQI. These steps are the selection of parameters, the generation of sub-indices, the generation of parameter weights and the aggregation process to compute the final index value. From the 30 reviewed WQIs, 7 were identified as most important based on their wider use and they were discussed in detail. It was observed that a major factor that influences wider use of a WQI is the support provided by the government and authorities to implement a WQI as the main tool to evaluate the status of rivers. Since there is a lot of subjectivity and uncertainty involved in the steps for developing and applying a WQI, it is recommended that the opinion of local water quality experts is taken, especially in the first three steps (through techniques like Delphi method). It was also observed that uncertainty and sensitivity analysis was rarely undertaken to reduce uncertainty, and hence such an analysis is recommended for future studies.

Assessment of water quality along a recreational section of the Damour River in Lebanon using the water quality index

Considering that water is becoming progressively scarce, monitoring water quality of rivers is a subject of ongoing concern and research. It is very intricate to accurately express water quality as water quantity due to the various variables influencing it. A water quality index which integrates several variables in a specific value may be used as a management tool in water quality assessment. Moreover, this index may facilitate communication with the public and decision makers. The main objectives of this research project are to evaluate the water quality index along a recreational section of a relatively small Mediterranean river in Southern Lebanon and to characterize the spatial and temporal variability. Accordingly, an assessment was conducted at the end of the dry season for a period of 5 years from 2005 to 2009. The estimated water quality index classified the average water quality over a 5-year period at the various sites as good. Results revealed that water quality of the Damour River is generally affected by the anthropogenic activities taking place along its watershed. The best quality was found in the upper sites and the worst at the estuary. The presence of fecal coliform bacteria in very high levels may indicate potential health risks to swimmers. This study can be used to support the evaluation of management, regulatory, and monitoring decisions.