Biological Water Quality Parameters Research Articles

Analysis of Residential Well Water Quality Around People's Gold Mines in the Tourist Area of Dusun Selindungan

The Sekotong area has natural charm and potential mining. This area is one of the preferred destinations for visits by local and foreign tourists. However, apart from that, the Sekotong area is also famous as a community gold mining area. Mining activities carried out still use traditional methods, which are very far from environmentally friendly principles, so they can have impacts, including causing a decrease in the quality of residential well water. This research was conducted to determine the water quality of residential wells around community gold mining in the tourist area of Dusun Selindungan Eleven well water samples were taken using a purposive sampling method based on the distance of the well to the source of gold mining waste disposal and are still used by residents to meet their daily needs. Physical, chemical and biological water quality parameters of water samples were investigated in the laboratory, except temperature and pH were measured directly in the field. Data for each water quality variable was analyzed to determine the pollution index. The results show that DO, TDS, content of phosphate, E. Coli bacteria and total coliforms in well water from the study area generally exceed quality standardsWell water in an area that is a different distance from the people's gold mining waste disposal site has each been contaminated with manganese and mercury, although it is still below quality standards.

Assessment of Water Quality Parameters in Lake Hayq, Northeastern Ethiopia.

Lake Hayq is one of the highland lakes of Ethiopia that furnishes very important ecosystem services, fishing, tourism, transportation, drinking water, livestock watering, and irrigation. However, the lake ecosystem is being degraded by pollution, siltation, and excessive growth of macrophytes, buffer zone degradation, overfishing, and climate variability. Therefore, this study was conducted to assess the physicochemical, heavy metals, and biological water quality parameters of Lake Hayq. Physiochemical (pH, water temperature, conductivity, TDS, total alkalinity, dissolved oxygen, Ca2+, Mg2+, Na+, K+, NH4+, NH3, NO2 -, NO3 -, CO3 -, HCO3 -, SO4 2-, PO4 3-, SiO2, and total phosphorus), heavy metals (Pb, Fe, Zn, Cr, Cu2+, Mn2+, and Ni), and biological (BOD5 and total coliforms) water quality parameters were analyzed both in situ and ex situ. The physicochemical parameters were measured using portable water quality measuring multimeters, the heavy metal analysis was done using the Atomic Absorption Spectrometer, the BOD5 was measured using a BOD5 meter, and the total coliform analysis was done using the spread plate technique. The collected data were analyzed using multivariate, two-way ANOVA to see the mean difference among sampling sites and seasons through the application of SPSS 16. Most of the water quality parameters of Lake Hayq have met the WHO standards for recreation, aquatic life, and drinking water quality. However, some parameters, such as Pb, BOD5, and total coliforms, were above WHO water quality permissible limits. Therefore, ecohydrological (nature-based) waste treatment methods such as macrophyte restoration in buffer zones and ecofriendly farming activities should be practiced to minimize the contamination of the lake.

Effect of Water Storage Tank Material on Quality of Water with Storage Period

Quality drinking water is of prime importance for human need. Potable water comes from surface water and groundwater sources and it is acceptable for human consumption. The method of storing water plays a crucial role in maintaining its purity and safety for human consumption. Due to lack of continuous water supply, storage tanks are necessary to store water and storage tank material may affect the quality of potable water. The objective of this study is to investigate the variation in water quality during storage for some particular time period in different types of storage containers. 40 days (six weeks) is considered to determine potable water quality variation during storage in different container materials and materials used for containers are plastic tanks, clay pot and Reinforced Cement Concrete. To find the water quality parameters, samples are to be collected at five days interval. During the period of storage, physical, chemical and biological water quality parameters are to be determined. Parameters obtained from above tests are analyzed to understand the effect of age and container material on the quality of potable water. This analysis is useful to choose the material of storage container to store water for a particular period of time.

Biológiai vízminőségi paraméterek hatásainak vizsgálata a szarvasi Holt-Körösön

One of the essential natural resources is water resource in Hungary. It is threatened by many threats, both quantitative and qualitative. For these reasons, the protection of surface water and groundwater is a priority. The main objective of the present study is to determine which parameters have the greatest influence on the horizontal and vertical distribution patterns of phytoplankton in the water body. The study area is the Holt-Körös, which plays an important ecological, social, economic and recreational role in the region. Between the field and laboratory tests, the following physical, chemical and biological water quality parameters were investigated: water temperature, UV radiation index, Secchi depth, underwater light condition, dissolved oxygen content, suspended solids content, chlorophyll-a content, Fe, NO2-, NO3- NH4+, PO43-, Na+, K+, Mg2+, and pH value.

Analysis of Water Quality and Phagocytic Activity (Clarias Sp.) in Aquaponic and Non-Aquaponic Cultivation Systems

Catfish (Clarias sp.) is one of the many fishery biota that has animal protein which is much loved by Indonesian people. One way to develop environmentally friendly catfish cultivation is through the implementation of an aquaponic biofilter system. This research aims to analyze physical, chemical, and biological water quality parameters in catfish cultivation with and without aquaponics, to obtain a description of the non-specific immune system which is analyzed from the conditions of phagocytic activity of catfish cultivated with and without aquaponics. The method used is by taking samples ten times per week by taking water quality parameters as well as blood samples of catfish raised in ponds with and without aquaponics. The analysis used is the unpaired T-test. Based on the results obtained, it was concluded that all parameters showed that the aquaponic cultivation media was better compared to those without aquaponics.

Effect of floating balls on evaporation inhibition, surface energy balance and biological water quality parameters at different coverage fractions

Effect of floating balls on evaporation inhibition, surface energy balance and biological water quality parameters at different coverage fractions

Cypermethrin insecticide residue, water quality and phytoplankton diversity in the lychee plantation catchment area

<abstract> <p>Lychee plantation areas are typically located at varying elevations on mountains to ensure proper drainage. This placement has direct effects on stream and river water flows and consequently influences pesticide residue, water quality and aquatic biodiversity. This research aims to examine the relationships between cypermethrin residue, water quality and phytoplankton diversity in the lychee plantation catchment area in Phayao Province, Thailand, from January to May 2022. The study area was divided into six sampling sites. Water samples were collected for the investigation of cypermethrin residual, physicochemical and biological water quality parameters. The water quality index was used as an overall measurement of water quality. The study also examined the diversity of phytoplankton species and the relationship among cypermethrin residue, water quality and phytoplankton diversity were studied using canonical correspondence analysis. The findings revealed an increasing trend of cypermethrin residue, with the maximum concentration reaching 29.43 mg/L in March. The trend of decreasing water quality scores from Station S1 to Station S5 indicated the influence of land use changes and human activities, especially in the community area (S5), which was characterized by deterioration of water quality. A total of 174 phytoplankton species were categorized into 5 divisions, with Chlorophyta accounting for 61.49% of the total, followed by Bacillariophyta (28.16%) and Cyanophyta (6.32%). The highest Shannon's diversity index and evenness were observed at Stations S3 and S4, respectively. The canonical correspondence analysis revealed an interesting relationship among cypermethrin residue, ammonia nitrogen, chlorophyll a and three algal species: <italic>Pediastrum simplex</italic> var. <italic>echinulatum</italic>, <italic>Pediastrum duplex</italic> var. <italic>duplex</italic> and <italic>Scenedesmus acutus</italic> at Station S3. This research implies that pesticide residue and water quality have a direct impact on phytoplankton distribution, illustrating the environmental challenges that occur in various geographical areas. This information can be applied to assist in the development of future sustainable land use management initiatives.</p> </abstract>

Comparative Study of Laboratory Based Chlorophyll - A Determination Methods

Protecting the quality and quantity of the available surface water resources is one of the most important points. Water quality is a complex concept that includes the physical, chemical, biological and hydrological parameters of water. One of the most significant biological water quality parameters is the chlorophyll-a content. Several different laboratory and field measurement methods are used to determine the chlorophyll-a content of water samples. The most frequently used laboratory methods are the Felföldy 1987 and the ISO 10260:1992 methods. Among field determination methods, submersible probes are frequently used to measure the chlorophyll-a concentration. Previously mentioned methods are based on fluorescence techniques. The main aim of this recent study is to compare different laboratory chlorophyll-a determination methods. Among the applied approaches, the Felföldy 1987 method and the ISO 10260:1992 method were compared. Furthermore, we measured the effect of the different solvent on the determination methods. Based on this, we investigated the Felföldy determination method using different solvents (methanol substituted with ethanol). The measurements were carried out under the same conditions from samples of Chlorella vulgaris culture in three repetitions by preparing a dilution series.

Effects of floating covers used for evaporation suppression on reservoir physical, chemical and biological water quality parameters

AbstractIncreasing demand for freshwater in arid regions with chronic water shortage calls for expansion of water storage for drought periods while protecting storage from evaporative losses. A cost‐effective and scalable method for evaporation suppression uses floating elements; however, little is known regarding biochemical and water quality effects under these covers. Two identical reservoirs with area of 25 m2 and depth of 2 m were used to investigate the influence of floating covers on water quality parameters for a period of one year (2019–2020). One of the reservoirs was covered with Styrofoam discs, and results were compared with the uncovered one. Results showed that the evaporation suppression efficiency of floating discs gradually decreased from 80% in spring to about 60% in winter. The comparison between reservoirs revealed that the presence of floating covers decreased pH, electrical conductivity (EC), total dissolved solids (TDS) and dissolved oxygen by 11%, 11%, 15% and 36%, respectively. We observed an increase in nitrate (30%), phosphate (27%) and ammonia (95%) concentrations in the covered reservoir. Results also demonstrated more concentration of biological populations such as algae and protozoa in the uncovered reservoir. The findings highlight improvement of certain water quality parameters in covered reservoirs such as EC and TDS with potential impacts on irrigation systems and soil health and salinity constraints.

Effect of 45 full-scale WWTPs on tropical receiving water bodies in Brazil by partial least squares-discriminant analysis

Abstract Treated wastewater may affect water quality and thereby significantly alter physicochemical and biological water quality parameters. The impact of wastewater treatment plants (WWTPs) on receiving water bodies is a multivariate problem. In this study, we investigated the effect of 45 full-scale WWTPs on tropical receiving water bodies in Mato Grosso do Sul State, Brazil. Most of the Pantanal wetland area lies within Mato Grosso do Sul State, thus representing a region of great hydrological relevance. Partial least squares-discriminant analysis (PLS-DA) was employed to discriminate samples collected at four WWTPs monitoring sites: influent, final effluent, upstream, and downstream of the discharges. The model demonstrated excellent accuracy when discriminating the influent from the effluent samples, but poor accuracy when discriminating upstream and downstream samples, indicating the high dilution capacity of the receiving water bodies as a critical factor in the water resources management. The results demonstrate the great potential of the methodology for better water resources management, which can be used in even more complex WWTP databases, allowing the assessment of effluent disposals' impacts in detail. It is recommended to use this methodology in water-limited regions to determine the effect of disposals in areas with different characteristics.

Remote sensing and machine learning based framework for the assessment of spatio-temporal water quality in the Middle Ganga Basin.

Understanding the dynamics of water quality in any water body is vital for the sustainability of our water resources. Thus, investigating spatio-temporal changes of dominant water quality parameters (WQPs) in any study is indeed critical for proposing the appropriate treatment for the water bodies. Traditionally, concentrations of WQPs have been measured through intensive fieldwork. Additionally, many studies have attempted to retrieve concentrations of WQPs from satellite images using regression-based methods. However, the relationship between WQPs and satellite data is complex to be modeled accurately by using simple regression-based methods. Our study attempts to develop a machine learning model for mapping the concentrations of dominant optical and non-optical WQPs such as electrical conductivity (EC), pH, temperature (Temp), total dissolved solids (TDS), silicon dioxide (SiO2), and dissolved oxygen (DO). In this context, a remote sensing framework based on the extreme gradient boosting (XGBoost) and multi-layer perceptron (MLP) regressor with optimized hyper parameters (HPs) to quantify concentrations of different WQPs from the Landsat-8 satellite imagery is developed. We evaluated six years of satellite data stretching spatially from upstream to downstream Ankinghat to Chopan (20 stations under Central Water Commission (CWC), Middle Ganga Basin) for characterizing the trends of dominant physico-chemical WQPs across the four clusters identified in our previous study. Through the developed XGBoost and MLP regression models between measured WQPs and the reflectance of the pixels corresponding to the sampling stations, a significant coefficient of determination (R2) in the range of 0.88-0.98 for XGBoost and 0.72-0.97 for MLP were generated, with bands B1-B4 and their ratios more consistent. Indeed, these findings indicate that from a small number of in-situ measurements, we can develop reliable models to estimate the spatio-temporal variations of physico-chemical and biological WQPs. Therefore, models generated from Landsat-8 could facilitate the environmental, economic, and social management of any waterbody.

Continuous Performance Improvement Framework for Sustainable Wastewater Treatment Facilities in Arid Regions: Case of Wadi Rumah in Qassim, Saudi Arabia.

In arid regions such as Saudi Arabia, wastewater treatment (WWT) facilities (meeting promulgated standards) need to adapt their continuous performance improvement (CPI) for long-term sustainability. To achieve this, the facilities need to improve their performance to comply with more strict objectives for broader reuse applications of treated effluent. The present research proposes a CPI framework based on performance benchmarking process for the stepwise improvement of WWT facilities. A grey rational analysis water quality index (GWQI) based on exceedance probability was developed. For weights’ estimation of 11 physical, chemical, and biological water quality parameters, the entropy method effectively accommodated the changes in relative importance of the parameters with including additional future reuse applications. For existing effluent reuse scenarios of restricted and unrestricted irrigation, the GWQI values were found consistent with the modified version of the Canadian WQI (CWQI). The indices’ values (ranged between 0 and 100) greater than 80 showed the efficient operation of four WWT plants in the Qassim Region of Saudi Arabia. Two hypothetical CPI scenarios with future reuse applications (fish, livestock drinking, and recreation) showed an overall decline in the average (of four plants) values of the GWQI (97 to 78) and CWQI (85 to 60). CWQI predicted stricter results for the facilities with parameters’ concentrations exceeding the targets with larger margins and was found applicable for the CPI of WWT facilities in arid regions. For existing scenarios, the assessment results suggest the facilities to control and monitor the chlorination practice. For future targets, tertiary treatment needs to be enhanced for desired nutrients and total dissolved solids removal. The proposed CPI framework provides a platform to initiate the performance benchmarking process for WWT facilities at local or regional levels in Saudi Arabia and elsewhere.

Synergy between Satellite Altimetry and Optical Water Quality Data towards Improved Estimation of Lakes Ecological Status

European countries are obligated to monitor and estimate ecological status of lakes under European Union Water Framework Directive (2000/60/EC) for sustainable lakes’ ecosystems in the future. In large and shallow lakes, physical, chemical, and biological water quality parameters are influenced by the high natural variability of water level, exceeding anthropogenic variability, and causing large uncertainty to the assessment of ecological status. Correction of metric values used for the assessment of ecological status for the effect of natural water level fluctuation reduces the signal-to-noise ratio in data and decreases the uncertainty of the status estimate. Here we have explored the potential to create synergy between optical and altimetry data for more accurate estimation of ecological status class of lakes. We have combined data from Sentinel-3 Synthetic Aperture Radar Altimeter and Cryosat-2 SAR Interferometric Radar Altimeter to derive water level estimations in order to apply corrections for chlorophyll a, phytoplankton biomass, and Secchi disc depth estimations from Sentinel-3 Ocean and Land Color Instrument data. Long-term in situ data was used to develop the methodology for the correction of water quality data for the effects of water level applicable on the satellite data. The study shows suitability and potential to combine optical and altimetry data to support in situ measurements and thereby support lake monitoring and management. Combination of two different types of satellite data from the continuous Copernicus program will advance the monitoring of lakes and improves the estimation of ecological status under European Union Water Framework Directive.

Evaluation of groundwater quality and reverse osmosis water treatment plants in the endemic areas of Chronic Kidney Disease of Unknown Etiology (CKDu) in Sri Lanka

Community-based reverse osmosis (RO) water treatment plants are employed as an interim solution for producing safe drinking water for the endemic areas of Chronic Kidney Disease of Unknown Etiology (CKDu) in the rural dry zone of Sri Lanka. It is recognized that RO-treated groundwater diminishes the progression of CKDu; thus, proper maintenance of these RO plants would be indispensable to protect public health. The present study broadly investigated the quality of groundwater in CKDu-endemic areas, and the performance, operations, and maintenance of the RO plants which purified this groundwater. The feedwater (i.e., groundwater) and treated water from 32 RO plants in Anuradhapura District, comprising 27 in the CKDu high-risk (HR) region and 5 in the low-risk (LR) region, were analyzed for major chemical and biological water quality parameters. Alkalinity, hardness, and microbiological parameters in groundwaters exceeded the maximum allowable levels (MALs) for drinking in all study areas. Additionally, TDS and magnesium exceeded the MALs, exclusively in the HR areas. Elevated occurrence of magnesium-predominant hardness and ionicity in groundwater showed significant relations with the incidence of CKDu. All RO plants achieved high removal rates (>95%) for excessive chemical constituents in groundwater, but the recovery rates were fairly low (~46%). The current disinfection practices in RO plants were insufficient to ensure the microbial safety of the product water. Low demand for product water, scarcity of groundwater, lack of technical capacity of the local communities, poor maintenance practices and unplanned brine removal were the key issues related to RO plant O&M. Unless properly handled, the lack of rules and regulations for RO water treatment in the CKDu-endemic region could lead to numerous environmental and public health issues in the future.

Imprints of pandemic lockdown on subsurface water quality in the coastal industrial city of Tuticorin, South India: A revival perspective

Globally, the incidences of environmental improvements owing to seizing the anthropogenic activities during the lockdown have been reported through news articles and photographs, yet a formal scholarly study has been lacking to substantiate the imprints of lockdown. We hereby present the imprints of lockdown on water quality (both chemical and biological) parameters during the nationwide lockdown (COVID-19 epidemic) in India between 25th March to 30th May 2020. The present study describes the changes in chemical and biological water quality parameters based on twenty-two groundwater samples from the coastal industrial city of Tuticorin in Southern India, taken before (10 and 11th February 2020) and during the lockdown (19 and 20th April 2020) periods. The physico-chemical parameters compared are pH, total dissolved solids (TDS) and electrical conductivity (EC), nitrate (NO3), fluoride (F), chromium (Cr), iron (Fe), copper (Cu), zinc (Zn), cadmium (Cd), lead (Pb), arsenic (As), and selenium (Se), and the bacterial parameters are total coliforms, fecal coliforms, E. coli, and fecal streptococci. Among the metals, the significant reductions in Se (42%), As (51%), Fe (60%) and Pb (50%) were noticed probably owing to no or very less wastewater discharges from metal-based industries, seafood-based industries and thermal power plants during the lockdown. Reduction in NO3 (56%), total coliform (52%) and fecal coliforms (48%) indicated less organic sewage from the fishing industries. Contents of Cr, Cu, Zn and Cd, however, remained similar and fluoride did not show any change, probably as they were sourced from rock-water interactions. Similarly, we did not observe alterations in E. coli and fecal streptococci due to no significant change in domestic sewage production during the lockdown. The multivariate analyses aptly illustrated this and the principal component analyses helped to identify the sources that controlled water qualities of the lockdown compared to the pre-lockdown period. Our observation implies that groundwater is definitely under active interaction with surface waters and thus a quick revival could be observed following the seizing of anthropogenic activities.

Principal Component Analysis for Water Quality Assessment of the Ganga River in Uttar Pradesh, India

The present study is an attempt to apply principal component analysis (PCA) for spatial assessment of water quality parameters that are responsible for water quality deterioration in the Ganga river at four cities of Uttar Pradesh. 48 water samples of the Ganga river from Allahabad, Mirzapur, Shahzadpur and Varanasi in Uttar Pradesh were collected during January to December in 2013. Data were analyzed for assessment of 18 different physicochemical and biological water quality parameters. These variables were examined using PCA to define and standardize the parameters mainly responsible for water quality variance in Ganga river at four selected cities. PCA highlighted anthropogenic effect and industrial effect as two main significant components which explain more than 99.32% of the variance, accounting for 64.47 and 34.85% respectively of the total variance of Ganga water quality at the four cities. Results revealed that total dissolved solids, total alkalinity, total hardness were the important parameters in assessing variations in Ganga water quality during October to April (post-monsoon months) and turbidity, suspended solids are the important parameters in assessing variations in Ganga water quality during June to September (monsoon months). Ca2+, Cl–, $${\text{SO}}_{4}^{{2 - }}$$ , temperature, fluoride, pH, Fe, Cl–, were found to be non-principal water quality parameters. Principal component analysis produced three significant main components explaining more than 82.9% of the variance (anthropogenic and industrial effect) that present 57.1, 13.8 and 12% respectively of the total variance of water quality in Ganga river at the four selected cities. The result reveals that turbidity, dissolved oxygen and biochemical oxygen demand are the parameters that are most important in assessing variations of water quality. Water quality index based on eight parameters (turbidity, DO, BOD, COD, pH, TS, TSS and TDS) calculated for all four cities were found to range from medium to bad. Thus, this study illustrates the usefulness of multivariate statistical techniques for analysis, interpretation of complex data sets and understanding spatial variations in water quality for effective river water quality management.

Assessment of the microbiological quality of rain water: A case study of selected water scarce area in Bangladesh

Availability as well as access to drinking water is one of the considerable constraints for achieving sustainable goals in many countries while microbial contamination has exacerbated this issue more significantly. The increasing trend of population and industrialization for economic growth has adversely been affecting fresh water resources that eventually leading to scarcity of available drinking water. Hence, controlling water pollution along with focusing on alternative water sources are important for ensuring access to safe drinking water. This study aimed to determine the biological water quality parameters of rainfall water in the water-scarce areas of Bangladesh. About sixty rainwater samples collected from seven different districts were collected for microbial analysis in particular Total Coliform (TC) and Fecal Coliform (FC) by using membrane filtration and direct counting method. The result found that 70 % of samples were free from total coliform, whereas only 5 % samples showed above 100 colonies. On the other hand, 83% samples were free from fecal coliform, whereas only 2% samples were within the range of 11-100 colonies. This study has also revealed that most of the samples collected from Rangamati and Khulna district were free from total coliform and fecal coliform. This study may also encourage people living in these water scarce areas to come forward for rainwater harvesting system as a prospective tool for achieving sustainable goal in drinking sector of Bangladesh.
 Stamford Journal of Microbiology, Vol.8(1) 2018: 24-26

Citizen science in Lebanon-a case study for groundwater quality monitoring.

Over the past decade, several citizen science projects have been launched, with a smaller subset addressing citizen scientists' involvement in water quality monitoring. Most of these projects were conducted in developed countries and focused on qualitative assessment and measurements of a limited number of water quality parameters. Moreover, data generated by citizen scientists were mainly for monitoring purposes and rarely resulted in remedial measures. In this work, a collaborative citizen science approach involving local citizens and university researchers was applied to assess the groundwater quality in a Lebanese village. Using a mobile laboratory, winter and summer sampling campaigns were conducted and 12 physical, chemical and biological water quality parameters were tested. Results indicated that the data generated by the citizen scientists were comparable with those generated by university researchers for the majority of physical and chemical water quality parameters. However, the bacteriological test results showed a marked difference and may be attributed to the complexity of the testing procedure and quality of testing material. The collaborative and participatory approach resulted in building local capacity and knowledge and in the formation of a locally elected water committee which will be responsible for continuous monitoring of the groundwater resources.

Application of Artificial Neural Network to Predict the Water Quality Index of Brahmani River Basin Odisha, India

Water is one of the prime elements responsible for subsistence on the earth. The scarcity of potable water is gradually increasing with the increase in population. The surface water quality is a very crucial and sensitive issue and is also a great environmental concern worldwide. Surface water pollution by physical, chemical, radiological and biological contaminants can be considered as an epidemic at times, all over the world. The present research work aims at assessing the water quality index (WQI) in the surface water of Brahmani river basin in Odisha by monitoring five sampling locations. The surface water samples data were subjected to comprehensive physico-chemical analysis besides general parameters. The monthly water quality parameters were collected and analyzed from five selected gauging stations of Odisha during the months of January to December from 2011 to 2016. Eleven physical, chemical and biological water quality parameters viz. pH, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Electrical Conductivity(EC), Nitrogen as nitrate (Nitrate-N), Total Coli-form Bacteria(TC), Fecal Coli-form Bacteria(FC), Chemical Oxygen Demand (COD), Nitrogen as ammonia (NH4-N), Total Alkalinity (TA) as CaCO3, Total Hardness (TH) as CaCO3 were selected for the analysis. Analysis of water quality for Brahmani River is done by Water Quality Index (WQI). Prediction of water quality index is done by using Artificial Neural Network (ANN). It is apparent from WQI values that Talcher and Panposh recorded the water quality as moderate to poor and nearly unsuitable during the years 2011-2016 indicating water as not safe for domestic purposes and needs treatment, the WQI values of Kamalanga ranged from good to poor and the WQI values of Aul and Pottamundai ranged from good to moderate. Eleven physico-chemical parameters were involved in this analysis as input variables and water quality index as output variable. Two models were proposed to identify the most effective model in an attempt to predict the WQI. Correlation between the parameters was carried out to find out the significant parameters affecting WQI. The ANN developed was trained and tested successfully using the available data sets and the performance of ANN models were determined by coefficient of determination (R2) and Root Mean Square Error (RMSE). Results show that ANN-1 gives the higher value of R2 in summer, monsoon and winter season (0.989, 0.976 and 0.959) and low RMSE (2.1865, 2.0768 and1.9657) as compared to that of the second model (ANN-2) which gives R2 value as 0.933, 0.945 and 0.943 and RMSE value as 2.8765, 2.5456 and 1.2745 for summer, monsoon and winter seasons respectively. Hence this study triggered the use of Artificial Neural Network to predict the Water Quality Index (WQI) rather than using the traditional WQI equation.

Towards developing a river health index

A number of physical, chemical and biological water quality parameters are measured to understand quality conditions of a riverine environment. Various aggregation techniques have been used to reflect the combined effect of the existing or proposed quality levels. Water Quality Index (WQI) has been developed primarily for fresh water environments. Organic pollutants are not considered in many WQIs because analyses of organics are rather expensive. In general, fecal coliform and total coliform counts are measured to reflect biological contamination of water. With growing consensus on considering rivers as ecological entity, rather than merely a source of water for human consumptions, the emphasis is changing from water quality index (WQI) to River Health Index (RHI). As benthic macroinvertebrate species are differentially sensitive to many biotic and abiotic factors in river environment, macroinvertebrate community structure has commonly been used as indicator of stream water condition. A number of river health assessment methodologies have been proposed in past and several indices such as Ecological Health Index (EHI), Ecological Quality Index (EQI), Overall Index of Pollution (OIP) and River Pollution Index (RPI) have been developed using water quality variables and aquatic species for evaluating the ecological health of river systems. This paper attempts to review and summarize some of these indices with particular emphasis on measurable parameters included in such formulations. The analyses suggest that with sufficient scientific experience and understanding in this area, it is possible to define a River Health Index (RHI) by including algae, macroinvertebrates and fish species as measurable parameters along with routine physico-chemical characteristics of river water. One such formulation on RHI has been proposed by the authors in this paper. The novelty of the proposed formulation include simple calculations and presentation of RHI value on 0–100 scale. The biological indices used in ACEDP (2011) requires biological expertise which is not normally available with water resource managers. Hence species identification and counting based simple biotic indices have been proposed so that it can be easily done by non experts also. River Health Level (RHL) can be categorized as ‘critical’ or ‘excellent’ based on RHI value <=20 or >80. Thus RHI values can be used to identify the healthy or unhealthy stretches of the river. RHI can serve as scientific tool to assess the current status, need and effectiveness of any intervention required to improve the condition of the river. Application of this RHI formulation on main stream of river Ganga (India) is under study.