Physicochemical Water Quality Parameters Research Articles

Assessment of water quality of Kot Dam, Rajasthan, India, using water quality index

Aim: To assess the water quality of Kot Dam, located in the Jhunjhunu district of Rajasthan, India. Methodology: Physico-chemical parameters of water quality were monitored for two years (July 2021 to June 2023). The Water Quality Index (WQI), a widely accepted mathematical expression used to understand the trend in the quality of water bodies, was calculated based on the analysis of physicochemical parameters, including pH, total dissolved solids, hardness, alkalinity, dissolved oxygen, biological oxygen demand, chloride, sulphate, nitrate, calcium, magnesium, conductivity, and fluoride. Results: The site-wise and season-wise analysis of WQI revealed that Dam water was polluted due to organic pollutants, agricultural runoff, and waste disposal by local people, especially during summer (WQI=87.18) and monsoon seasons (WQI=85.38). Interpretation: Anthropogenic activities adversely affected the water quality at sample station (S1) of Kot Dam. Key words: Anthropogenic activities, Bray-Curtis Similarity Index, Dendrogram, Kot dam, Water quality

Phytoplankton functional dynamics in relation to some physicochemical parameters in Lake Kuriftu (Oromia, Ethiopia)

The water quality of Lake Kuriftu is deteriorating, and monitoring programs are almost nonexistent in Ethiopia. Phytoplanktons are good indicators of environmental changes due to their fast response to a wide range of stressors. The phytoplankton functional groups (FGs) can be used as water quality indicators. This study aimed to assess the dynamics of phytoplankton functional groups (FGs) in relation to some physicochemical water quality parameters measured at three sites in Lake Kuriftu. Samples for the analysis of biological and physicochemical parameters were collected monthly, from December 2020 to April 2021. The results of the physicochemical parameters revealed that Lake Kuriftu is turbid (21.37 to 59.86 NTU), has a thin euphotic depth (ZSD0.304 to 0.548 m), and is eutrophic. Ninety-seven (97) phytoplankton taxa were identified and classified into 16 Reynolds Functional Groups (RFGs), of which six (J, MP, X1, Lo, S1, and F) were represented by more than six species. FGs S1, SN, Lo, and Lm, which often form Harmful Algal Blooms, contributed together about 33.54 mg L−1, or 87.84 %, of the total biomass recorded for Lake Kuriftu, demonstrating the water quality of the lake is deteriorating. Among the FGs, the most dominant (in terms of biomass) was S1, followed by J at all sites and in all sampling months. The results of redundancy analysis (RDA) revealed that the main driving factors of phytoplankton FG biomass and composition were TP, ZSD, TN, Salinity, and ammonia. Among these, TP and salinity impacted the FGs negatively, while TN and ammonia influenced them positively. Thus, the physicochemical parameters have a significant impact on the distribution of phytoplankton FGs, suggesting that the use of FGs for water quality monitoring programs is useful. To promote wise use and conservation of the lake ecosystem, more intensive study should be carried out on the biological and physicochemical aspects of the lake, as it is part of a tourist attraction area and a source of income for local inhabitants.

Plankton Diversity and Hydro-biological Parameters at Wazirabad Barrage in Yamuna River

This study conducted a comprehensive investigation into the qualitative and quantitative analysis of plankton diversity and Physico-chemical water quality parameters in the Yamuna River. Samples were collected from the Wazirabad barrage from June 2022 to November 2022, revealing a diverse phytoplankton community consisting of 50 genera distributed across five major classes. The abundant classes were Bacillariophyceae, with 18 genera, followed by Chlorophyceae with 20 genera, Cyanophyceae with 9 genera, Euglenophyceae with 2 genera, and Dianophyceae represented by a single genus. The qualitative analysis uncovered a zooplankton community with 20 genera from Protozoa and Rotifera, Copepoda, and Cladocera. Protozoa were represented by two genera, Copepods exhibited eight genera, Cladocera included five genera, and Rotifera featured four genera. The most abundant class of phytoplankton is Chlorophyceae and Zooplankton is Copepods. Physico chemical water quality parameters more fluctuation during the study period. These findings offer valuable insights into the biodiversity and composition of phytoplankton and zooplankton communities in the Wazirabad Barrage ecosystem.

Integrated Assessment of Kirala Kele Wetland Health: Bridging the Gap between Water Quality Parameters and Biotic Components

Abstract The present study was carried out to assess the health of the Kirala Kele Wetland, Sri Lanka, by coupling water quality indices and bioindicators. A total of 12 sampling sites were selected to represent different land-use patterns of the Kirala Kele Wetland using purposive sampling technique, and sampling was conducted from March 2021 to May 2021, on a monthly basis. Triplicated samples (n = 3) were obtained for each sampling event at each sampling site. Aquatic macroinvertebrates were collected from each site to determine the biological water quality using the Biological Monitoring Working Party (BMWP) score. Weighted Arithmetic Water Quality Index (WAWQI) was calculated to understand the physicochemical parameters of water, and the mean values of physicochemical water quality parameters were compared with the Sri Lankan water quality standards. According to the WAWQI for the different sampling sites, water is not suitable for drinking without treatment. The resulted BMWP score (BMWP = 61) shows that the water quality is acceptable (clean but slightly impacted) for biotic components of the wetland in accordance with the aquatic macroinvertebrates present. Spatial variation in water quality parameters and the aquatic macroinvertebrates were taken into account, and the temporal variation in water quality parameters within the 3 months from March to May was considered.

Comparison of the zooplankton-based RCC to Carlson’s trophic state indices and water quality parameters

Zooplankton is not included as a biological quality element, even though it is a key component of pelagic food webs. The data on zooplankton community structure can be used to evaluate the trophic state of lakes through an RCC Index, based on quantitative proportions between the main zooplankton groups. As previous investigations have related the index only to the Secchi disc transparency, the aim of this study was to compare the Index to a set of water quality parameters and trophic state indices. Two sandpit lakes with contrasting characteristics were selected as model lakes for the study. A total of 57 samples were collected simultaneously with the physicochemical water quality parameters between 2016 and 2020. Carlson’s trophic state indices were used to assess the trophic state of the lakes. Pearson correlation coefficient and Principal Component Analysis were used to assess the observed correlations between the measured parameters and to distinguish what factors regulate zooplankton community structure. Overall, 86 zooplankton taxa were identified. RCC Index ranged from 2 in the small sandpit lake to 87 in the big sandpit lake. A highly significant negative correlation was found between the RCC Index and the values of TP and COD. The results complement the arguments for the inclusion of zooplankton as a BQE for the assessment of the status of lakes.

Use of Fish Somatic Indices to Assess Pollutant Exposure and Effects: A Case of Two Urban Rivers and a Wastewater Sedimentation Pond in Lake Victoria Basin

Aquatic ecosystem health assessment is critical for early detection of disturbances and water habitat degradation. This study assessed the ecological status of two urban rivers as well a wastewater sedimentation pond in Kisumu City, Kenya using physico-chemical water quality parameters and the African catfish, Clarias gariepinus somatic indices. Site association of somatic indices was derived from Principal Component Analysis (PCA) whereas the relationship between water quality parameters was examined by Redundancy Ordination Analysis (RDA). PCA results revealed an increase in Gill Somatic Index (GSI) in the wastewater sedimentation ponds while Fulton’s Condition Factor (CF) increased in the midstream of Auji river and Kisat river mouth. Similarly, RDA showed that dissolved oxygen, temperature, total phosphorus, alkalinity and total nitrogen influenced the condition indices upstream of Kisat river and up-stream and midstream of Auji river. However more impact on somatic indices were recorded in the wastewater sedimentation pond. Although specific pollutants other than the physico-chemical parameters were not identified, application of somatic indices in the African catfish demonstrated that the two rivers as well as the wastewater sedimentation pond were contaminated by pollutants that can compromise the ecological health of the aquatic systems. The results of this study emphasized the negative impacts of anthropogenic activities on the environment.

Prediction of chlorophyll-a as an indicator of harmful algal blooms using deep learning with Bayesian approximation for uncertainty assessment

Data-driven models are efficient decision support tools for monitoring harmful algal blooms (HABs), particularly with the advent of the Internet of Things (IoT) and continuous data acquisition sensing systems. While high chlorophyll-a concentrations in freshwater systems are often used as an index of HABs, diurnal variations in physicochemical water quality parameters influence chlorophyll-a concentrations in these systems. Previous studies have demonstrated the effectiveness of deep learning models in predicting chlorophyll-a as an index of HABs. However, predicting HABs before they occur often comes with uncertainties related to the frequency of observed data. This study used varying sampling periods to develop various Long Short-Term Memory (LSTM) models coupled with a Monte Carlo dropout scheme to estimate model uncertainties for chlorophyll-a predictions in a freshwater lake. The model’s performances were compared using indices such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and correlation coefficient. The results showed that while a daily water quality dataset predicted chlorophyll-a concentrations 3-days in advance with the conventional 0.2 dropout rate, an hourly dataset predicted chlorophyll-a concentrations 7-days in advance. When the effect of the sampling period was considered, the full dataset (both daytime and nighttime datasets combined) provided better chlorophyll-a predictions compared to the model that only used either the daytime or nighttime dataset. This research outcome will assist in predicting HABs timely using chlorophyll-a as an index, aid in developing early warning systems, and understand the data-sampling, data-transmission, and data-storage needs, which are often the critical elements for data-driven modeling.

Physicochemical Parameters of Ground Water Quality in Crown Estate and Its Environs in Okada Town, Edo State, Nigeria

The evaluation of drinking water quality mainly by determination of some physicochemical parameters present is of paramount importance due to the impact on human health. The present study presents investigation on the physicochemical parameters of ground water samples collected from selected boreholes, in Crown Estate and environs, in Okada, Benin City, Nigeria. Samples were collected from selected boreholes and pH taken and immediately taken to the laboratory to investigate some selected physicochemical characteristics. The mean concentrations of metals in the water samples followed a decreasing order: Zn (0.5122mg/l) > Fe (0.4378mg/l) > Mn (0.0594mg/l) > Ni (0.0358mg/l) > Cr (0.0302mg/l) > Cu (0.3000mg/l), Pb and Cd were below detection limit. The laboratory results of all the selected physico-chemical parameters analyzed when compared with the world health organization (WHO), National Agency for Food and Drug Administration Control (NAFDAC) and Nigerian Standards for Drinking Water Quality (NSDWQ) standards for water showed that all the selected Physicochemical parameters with the exception of iron (for NAFDAC) were within national and international standards limits for drinking water.

Assessing Groundwater Level and Water Quality in Bhaktapur Municipality: A Pre-Monsoon and Post-Monsoon Analysis

Groundwater is a crucial natural resource for sustaining human life, agriculture, and ecosystems worldwide. In many Asian countries, including Nepal, groundwater has emerged as a dependable source of water, particularly in areas where surface water is scarce or unreliable. For instance, in Bhaktapur Municipality (BM), Nepal, groundwater has been contributing around 50–60% of the total water supply. However, over the past few years, extensive extraction, alterations in the land use pattern, and other anthropogenic interventions have posed serious threats to this highly valuable resource. As such, groundwater monitoring is an essential primary step for understanding the status of the groundwater resource. Meanwhile, the Water Quality Index (WQI) is an effective tool that can turn complex water quality data into simplified information that is understandable and usable by the public. This study aimed to understand the groundwater levels and further comprehend the groundwater quality using the WQI of the BM. The groundwater level data and water samples were collected from 24 spatially distributed wells of the BM in the post-monsoon of 2021 and the pre- and post-monsoon of 2022. Laboratory analysis was carried out to determine the nine physico-chemical water quality parameters, and the obtained parametric values were compared with those of the World Health Organization (WHO) and the National Drinking Water Quality Standard (NDWQS). The results show deeper groundwater levels in the core area than the periphery, and the water quality getting poorer from post-monsoon 2021 to post-monsoon 2022. The EC, TDS, pH, phosphate, chloride, and hardness of most of the samples were within the permissible limits of WHO and NDWQS, whereas the turbidity, ammonia, and alkalinity of many samples exceeded the permissible limits. Average WQI revealed that the majority of the samples were unsuitable for drinking and suitable only for household and irrigation purposes. This study provides insights into managing water demands, addressing issues of water scarcity, and highlighting the urgent need for additional research and policymaking to improve drinking water quality and the sustainability of groundwater management in BM.

Predictions of heavy metal concentrations by physiochemical water quality parameters in coastal areas of Yangtze river estuary

Due to the degradation-resistant and strong toxicity, heavy metals pose a serious threat to the safety of water environment and aquatic ecology. Rapid acquisition and prediction of heavy metal concentrations are of paramount importance for water resource management and environmental preservation. In this study, heavy metal concentrations (Cr, Ni, Cu, Pb, Zn, Cd) and physicochemical parameters of water quality including Temperature (Temp), pH, Oxygen redox potential (ORP), Dissolved oxygen (DO), Electrical conductivity (EC), Electrical resistivity (RES), Total dissolved solids (TDS), Salinity (SAL), Cyanobacteria (BGA-PE), and turbidity (NTU) were measured at seven stations in the Yangtze river estuary. Principal Component Analysis (PCA) and Spearman correlation analysis were employed to analyze the main factors and sources of heavy metals. Results of PCA revealed that the main sources of Cr, Ni, Zn, and Cd were steel industry wastewater, domestic and industrial sewage, whereas shipping and vessel emissions were typically considered sources of Pb and Cu. Spearman correlation analysis identified Temp, pH, ORP, EC, RES, TDS, and SAL as the key physicochemical parameters of water quality, exhibiting the strongest correlation with heavy metal concentrations in sediment and water samples. Based on these results, multiple linear regression as well as non-linear models (SVM and RF) were constructed for predicting heavy metal concentrations. The results showed that the results of the nonlinear model were more suitable for predicting the concentrations of most heavy metals than the linear model, with average R values of the SVM test set and RF test set being 0.83 and 0.90. The RF model showed better applicability for simulating the concentration of heavy metals along the Yangtze river estuary. It was demonstrated that non-linear research methods provided efficient and accurate predictions of heavy metal concentrations in a simple and rapid manner, thereby offering decision-making support for watershed managers.

Occurrence of antibiotics and antibiotic-resistant bacteria in the Lebanese polluted Litani River.

Antibiotic contamination in polluted rivers is well recognized as an environmental and public health challenge. In this study, the occurrence, distribution, and ecological risk assessment of three commonly used antibiotics (amoxicillin, ciprofloxacin, and azithromycin) were assessed in the Litani River, the most important and highly polluted river in Lebanon. Physicochemical and microbiological water quality parameters including the antibiotic-resistant ones were in parallel determined in the same sites. Water samples from five sites stretching across the river upper basin were analyzed for the antibiotics under study using high-performance liquid chromatography, with both fluorometric and UV detectors post-extraction using a solid-phase method with a hydrophilic-lipophilic balance cartridges. The disc diffusion method and standardized water quality methods were used for antibiotic-resistant bacteria and water quality assessment, respectively. Amoxicillin and ciprofloxacin were found at concentrations of 250 ng/L and 107.2 ng/L, while azithromycin was not detected in any of the sites under study. Varying levels of antibiotic resistance were detected with the isolated Escherichia coli (E. coli) and Pseudomonas aeruginosa (P. aeruginosa) while the total coliforms showed resistance to multiple antibiotics. COD, TP, PO43-, TN, NO3-, NH4 + , E. coli, total coliform, P. aeruginosa, and Cd levels surpassed permissible levels. Correlation analysis with water quality parameters (COD, total phosphate, phosphate, total nitrogen, and cadmium) showed a significant positive correlation with ciprofloxacin (r > 0.5, p value < 0.05). Also, the resistant P. aeruginosa showed a significant positive correlation with cadmium (r > 0.5, p value < 0.05) while the resistant E. coli was positively correlated with total nitrogen, nitrate, and lead levels (r > 0.5, p value < 0.05). The ecological risk assessment revealed that all the tested antibiotics pose low risks (ecological risk quotient RQ < 0.1) except ciprofloxacin, which could pose a medium risk (0.1 < RQ < 1). Future research concerning the long-term assessment of antibiotics' residues and the identification of resistance genes in the river is recommended.

Integrating water quality monitoring and ecological assessment for wetland classification and risk evaluation in the Kirala Kele wetland, Sri Lanka

Abstract We conducted the present study to assess the spatial and temporal variations of selected physicochemical water quality parameters, to quantify the level of ecological risks of disturbances occurring, and to understand the relationship between the selected disturbances observed and physicochemical parameters of surface water of sampling sites of the Kirala Kele wetland. We selected sampling sites to reflect different land uses in the Kirala Kele wetland using purposive sampling and collected triplicated surface water samples to assess quality of water. The sampling sites of wetland characterization and risk assessment were followed using the protocol by Escom. We found that there was a significant temporal variation of pH, electrical conductivity, water temperature, and dissolved oxygen content among sampling sites (p &amp;gt; 0.05, One-Way ANOVA), however, spatial variation of electrical conductivity and dissolved oxygen was significantly higher in site 9, site 10, and site 11, respectively (p &amp;gt; 0.05, One-Way ANOVA). Site 2, site 5, site 10, and site 11 showed a category B level in wetland characterization and risk assessment highlighting the few levels of modifications and largely natural status of sites. The study demonstrates the applicability of this model for rapid assessment of wetland characteristics and risks to sustainably conserve and manage wetlands.

Machine learning-based water quality prediction using octennial in-situ Daphnia magna biological early warning system data

Biological early warning system (BEWS) has been globally used for surface water quality monitoring. Despite its extensive use, BEWS has exhibited limitations, including difficulties in biological interpretation and low alarm reproducibility. This study addressed these issues by applying machine learning (ML) models to eight years of in-situ BEWS data for Daphnia magna. Six ML models were adopted to predict contamination alarms from Daphnia behavioral parameters. The light gradient boosting machine model demonstrated the most significant improvement in predicting alarms from Daphnia behaviors. Compared with the traditional BEWS alarm index, the ML model enhanced the precision and recall by 29.50% and 43.41%, respectively. The speed distribution index and swimming speed were significant parameters for predicting water quality warnings. The nonlinear relationships between the monitored Daphnia behaviors and water physicochemical water quality parameters (i.e., flow rate, Chlorophyll-a concentration, water temperature, and conductivity) were identified by ML models for simulating Daphnia behavior based on the water contaminants. These findings suggest that ML models have the potential to establish a robust framework for advancing the predictive capabilities of BEWS, providing a promising avenue for real-time and accurate assessment of water quality. Thereby, it can contribute to more proactive and effective water quality management strategies.

Metabolomic response of striped marsh frog (Limnodynastes peronii) tadpoles exposed to the fire retardant Phos-Chek LC95W

Climate change and other factors have contributed to an increased frequency and intensity of global wildfires in recent years. Ammonium-based fire retardants are widely used to suppress or delay the spread of fire and have generally been regarded as presenting a low risk of acute toxicity to fauna. However, studies have raised concerns about their potential to cause indirect or sub-lethal effects, and toxicity information regarding the potential for such impacts in aquatic species is limited. To address these knowledge gaps, we used an untargeted metabolomics approach to evaluate the sub-lethal physiological and metabolic responses of striped marsh frog (Limnodynastes peronii) tadpoles exposed to a concentration gradient of the ammonium polyphosphate (APP)-based fire retardant Phos-Chek LC95W (PC). Acute exposure (96 h) to PC significantly altered the relative abundance of 14 metabolites in whole tadpoles. The overall metabolic response pattern was consistent with effects reported for ammonia toxicity and also suggestive of energy dysregulation and osmotic stress associated with alterations to physicochemical water quality parameters in the PC treatments. Results suggest that run-off or accidental application of this formulation into waterways can have significant sub-lethal consequences on the biochemical profiles (i.e., the metabolome) of aquatic organisms and may be a concern for frog species that breed and develop in small, often ephemeral, waterbodies. Our study highlights the benefits of integrating untargeted metabolomics with other ecological and toxicological endpoints to provide a more holistic characterisation of the sub-lethal impacts associated with bushfire-fighting chemicals and with environmental contaminants more broadly.

Interpretation of Ground Water Quality Parameters with correlation matrix of different sampling sites of Jaipur (Rajasthan)

Water is one of the utmost important constituents on earth. This study is based on physicochemical water quality parameters (pH, EC, TDS, TH, Ca2+ Mg2+, Na+, K+, F-, Cl- NO3-SO42-) biological Parameters (BOD, COD, DO) and calculation of water quality index to assess the water quality of a four sampling sites like Muhana (S1), Vatika (S2), Shivdaspura (S3) and Tiwadi (S4) of Jaipur (Rajasthan, India). Statistical analysis had been used to calculate the correlation coefficient of different parameters with WQI and determine the Irrigational nature of ground water. Among these parameters, EC has the highest positive correlation with Na+, Cl-, F- ion concentration whereas as TDS show strong negative correlation with Ca2+.

Interpretation of Diverse Physico-Chemical Water Quality Parameters of Jaipur (Rajasthan) Sampling Sites for Plantation, Irrigation and Fluorosis Concern

The present study is aimed to evaluate the hydro chemical characteristics and quality of groundwater. Groundwater samples were collected from selected sampling sites like Shivdaspura (S1), Mansarovar (S2), Tonk Phatak (S3) and Chand pole (S4) in Jaipur District, Rajasthan and analyzed for major physico-chemical parameters. Such as Colour vis, Chemical Oxygen Demand (COD), Bio-Chemical Oxygen Demand (BOD), Lead, Cadmium, Chloride, Fluoride, Dissolved Oxygen (DO), Total Hardness (TH), Total Alkalinity, Total Solids, Total Dissolve Solids (TDS), Total Suspended Solids, Taste and Odour, Turbidity, Electrical Conductivity (EC), Magnesium, pH, Nitrate, Calcium, Sulphate Were analysed fora period from 29March 2021 to 09 December 2021. Fluoride content in the water samples of study area varied from 0.57mg/l to 7.97mg/l. Due to the higher fluoride levels in drinking water of Shivdaspura area showing dental fluorosis in which the teeth of the children were damaged and characterized by brown and black stains.

Possible Pollution of Surface Water Bodies with Tequila Vinasses

The aim of this study was to evaluate the water quality in two streams of the Valles region of Jalisco, Mexico and fully determine if they are being used as tequila vinasse disposal sites. Three sampling campaigns were carried out at eight different points of the two streams that run near tequila factories (TFs). Different physicochemical parameters of water quality were measured: chemical oxygen demand (COD); biochemical oxygen demand (BOD5); total suspended solids (TSSs); total phosphates; fats, oils, and grease (FOG); Kjeldal nitrogen; nitrite; nitrate; pH; conductivity; temperature; dissolved oxygen (DO); and turbidity. Also, the analysis of samples of tequila vinasses (TVs) diluted with tap water were carried out to have a reference for the level of pollution in the streams. Furthermore, due to the fact that COD could be considered the main indicator of pollution with TVs, a linear regression was performed between COD concentrations and the percentage of dilution of TVs (with tap water). A positive correlation was found between these two variables, and based on this analysis, the vinasse content was estimated at each sampling point of the streams. It was found that on average, a volume of 8.5 ± 6.3% and 11.5 ± 4.9% of TVs were present in each sampling point of the Atizcoa and Jarritos Streams, respectively. Additionally, it was found that, in general, the concentration of pollutants increased as the streams passed through the TFs, particularly the Atizcoa Stream. According to the Water National Commission criteria, most of the points would be classified as highly polluted, since they reach concentrations of COD and BOD5 up to 6590 mg/L and 3775 mg/L, respectively, temperature values up to 37 °C, and DO values of 0.5 mg/L. Therefore, it was confirmed that the streams are being used as tequila vinasse disposal sites. Due to the above, there is an urgent need for tequila companies to implement treatment systems for the vinasse generated, since under current conditions, the monitored streams are practically devoid of aquatic life.

Assessment of Physico-chemical Parameters of water quality of Ground Water, Almanagil town, Gezira State, Sudan

The current study was conducted to evaluate physical and chemical parameters of water quality taken from some of ground wells in Almanagil town, Gezira State, Sudan. The efforts, in this work, included a collection of different groundwater samples from Managil town. Many groundwater samples were collected from different wells distributed throughout the area of study. From all these groundwater samples, only eight samples were selected, to exclude repetition, and subjected to physico-chemical analysis. The physical characteristics including: conductivity (EC) of the collected samples were determined. The values of different chemical parameters as: pH, total dissolved salts (TDS) were measured according to the standard methods of analysis. In addition, the concentration of many anions (chloride, nitrite, nitrate) were determined. Results showed that EC between 440 -601 (ppm), GH 1000 (mg/L) all, NO3 and NO2 0.00 (mg/L) , Cl2 range between 0.7-3.58 (mg/L) ,KH 120- 362.667 (mg/L) ,salts 18.0-20.0 % , pH has values ranged from 8.0 – 8.5 while the Total Dissolved Solids (TDS (mg/L)) between 6.67 – 12.0 (mg/L) whereas (TDS (ppm)) between524.33- 653.67 . The results revealed significant different at (P≤ 0.01) with exception of (NO3) value zero so (NO2) and GH (1000mg/L) were not significant at P&gt; 0.05). The findings show validity of certain samples for human uses.

Using hydrogeochemical facies and signatures for groundwater characterization and evolution assessment in aquifers with contrasting climate and geology in Tanzania

This study aimed at characterizing groundwater evolution using hydrogeochemical facies and signatures in two basins with contrasting climate and geology, one in the central part and the other in the eastern coast of Tanzania. The Kimbiji (humid, unconsolidated) aquifer is covered by an unconfined layer in the upper parts and a confined layer in the lower parts, with strong artesian flow characteristics while groundwater in the Singida (semi-arid, consolidated) aquifer occurs in weathered shallow layers and in fractures of basement rocks. Fieldwork involved water sampling from precipitation, deep and shallow boreholes, springs and surface water from rivers and lakes in the two study areas. These were specifically conducted for hydrogeochemical analyses to unravel hydrogeochemical facies and signatures in the two aquifers. Physico-chemical water quality parameters [i.e., pH, electrical conductivity (EC) and total dissolved solids (TDS)] were measured in situ using HANNA HI 9829 Multiparameter Analyzer. Standard procedures for water sampling, preservation, transportation, and chemical analyses of major ions were conducted as documented in previous studies. Samples were carried and stored at 4 °C prior to their shipping and analyses at Water analysis and testing in environmental regions (WATER) laboratory in Iringa, Tanzania. The mechanism controlling groundwater geochemistry were revealed by assessing the reactions between groundwater and aquifer minerals. Chloro-Alkaline indices (CAIs) were used to study cation exchange processes between the groundwater and its host environment at stagnancy and/or during groundwater travel. The Gibbs ratio 1 values were found to range from 0.26 to 0.94 and Gibbs ratio 2 values ranged from 0.11 to 0.95. The majority of the samples irrespective of the contrast in climate and geology were observed to fall in the rock–water interaction zone. This is attributed to chemical weathering processes where the dissolution of rock forming minerals takes place. Some samples exhibited replacement of Na+ by Ca2+ or Mg2+ (S18), loss of Na+ through precipitation of evaporate rocks (S11, S13, S16, S19), and water flowing through crystalline rocks (S1, S2, S4, S6, S8, S10, S12, S13, S14, S21). The ratio Na+: Ca2+ > 1.0 (S1, S4, S8, S10, S12, S14, S17, S18, S19, S21) explains base ion exchange while the ratio < 1 implies a reverse ion exchange (S2, S6, S11, S13, S16).The Ca2+: SO42− + HCO3− ratio < 1.0 connotes groundwater flowing through a normal hydrological cycle (S1, S4, S8, S10, S12, S14, S17, S18, S2, S6, S11, S13, S21) and a ratio greater than 1 is an indication of Ca2+–Cl− brines (S16, S19). The HCO3−: Cl− hydrogeochemical signatures divided the Singida aquifer into upper water flow course, where groundwater recharge occurs (S52, S54, S56, S57, and S58) and the discharge zone, (S53, S59, S60, S61) which is a lower groundwater flow course. Interestingly, the Mg2+ + Ca2+: Na+ + K+ ratios as well confirmed that the Singida aquifer is a lower groundwater flow course (discharge zone). The greater than 1 Na+: Ca2+ ratios confirm the dominance of base ion exchange in the Singida aquifer as it has been explained by the CAIs and the Piper diagram. The Gibbs diagrams revealed that the hydrochemistry of groundwater in the Kimbiji and Singida aquifers are mainly in the rock weathering region, affirming that there is high dissolution with rock forming minerals. This is thus one of the main controls of groundwater mineralization in the two study areas. The similarity of hydrogeochemical signatures between a distant surface water body, Lake Inkhanoda and Mwankoko borehole in the Singida aquifer is an indication that there is a discernible interaction between groundwater and surface water, further revealing that the Singida aquifer is fed by sub-regional and regional groundwater flow systems.

Application of Water Quality Index and Water Suitability for Drinking of the Euphrates River within Al-Anbar Province, Iraq

In this study water quality was indicated in terms of Water Quality Index that was determined through summarizing multiple parameters of water test results. This index offers a useful representation of the overall quality of water for public or any intended use as well as indicating pollution, which are useful in water quality management and decision making. The application of Water Quality Index (WQI) with ten physicochemical water quality parameters was performed to evaluate the quality of Euphrates River water for drinking usage. This was done by subjecting the water samples collected from seven stations within Al-Anbar province during the period 2004-2010 to comprehensive physicochemical analysis. The ten physicochemical parameters included: pH value, Alkalinity (ALK), Orthophosphate (PO4-3), Nitrate (NO3-),Sulphate (SO4-2), Chloride (Cl-), Total Hardness (TH), Calcium (Ca), Magnesium (Mg), and Total Dissolved Solids (TDS). The average annual overall WQI was found to be 107.59 through the study period. The high WQI obtained is a result of the high concentrations of Orthophosphate and Magnesium which can be attributed to the various human activities taking place along the river banks. From this analysis the quality of the Euphrates River is classified as "very poor quality" ranging poor water at the river upstream near station (E1) and unsuitable for drinking at the river downstream near station (E7) with an annual minimum WQI of 89.34 in 2008 and maximum 112.44 in 2009. The present study demonstrated the application of WQI in estimating and understanding the water quality of Euphrates River. WQI appears to be promising in water quality management and a valuable tool in categorizing pollution sources in surface waters