Comparative evaluation of river chemical status based on WFD methodology and CCME water quality index

Assessing flooding extent and potential exposure to river pollution from urbanizing peripheral rivers within Greater Dhaka watershed

Greater Dhaka area is home to large industrial clusters that are driving economic growth and the poverty reduction efforts of Bangladesh. These clusters are located around peripheral rivers- Turag, Buriganga, Dhaleswari, Balu, Shitalakhya, Bangshi, and Tongi-Khal, which are important for water transport, environment, and eco-systems where flooding of floodplains in monsoon is an integral part. The urban and industrial growth stressing natural resources has led to severe degradation of the rivers and floodplains, affecting the livelihoods, health, and well-being of the people. Monsoon-time exposure to polluted water is yet to be studied and addressed scientifically. This study looked into the water quality and flooding situation of Greater Dhaka for two successive monsoons through extensive river sampling coupled with the estimation of flooded area and exposed population using remote sensing tools. Sentinel 1's Synthetic Aperture Radar (SAR) images are used for flood mapping considering cost-effectiveness and its advantages for data-scarce regions. The estimated population exposed to flooding was over 668,000 in 2019, and this number increased by 1.53 times in 2020, totaling over one million. During the monsoon and post-monsoon periods of 2019 and 2020, Buriganga, Tongi Khal, and Balu were consistently in poor condition. The lowest water quality index (WQI) was observed in Balu during the monsoon of 2019 (32.28), post-monsoon of 2019 (35.71), and post-monsoon of 2020 (29.58). The lowest WQI during the monsoon of 2020 was recorded in Tongi Khal (35.75). Among the four districts, Dhaka and Gazipur were the most affected by floods in terms of inundation area and exposed population. Our study indicates that most rivers remain in poor condition during the monsoon when exposure is also high. This highlights the need for policymakers to take monsoon exposure seriously and design appropriate interventions.

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

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

Impacts of seasonal variations and wastewater discharge on river quality and associated human health risks: A case of northwest Dhaka, Bangladesh

Surface water pollution caused by the discharge of effluents from industrial estates has become a major concern for Dhaka (Bangladesh). This study aims to have a concise look at the severe river water pollution, mainly from effluents discharged from the tannery village. Effluent samples were collected from five ejected points, including the central effluent treatment plant (CETP), twenty adjacent river water, and two pond water nearby Hemayetpur, Savar. Thirty-one parameters have been observed at these sampling points for three seasons, from April 2021 to January 2022. The results obtained from water quality indices, i.e., water quality index (WQI), entropy water quality index (EWQI), and irrigation water quality index (IWQI), show that most studied surface water samples ranked "unsuitable" for consumption, irrigation, and anthropogenic purposes. The highest health risk was observed downstream of Hemayetpur city at the Savar CETP discharge site, indicating higher levels of heavy metal in the river water following the tannery village. Carcinogenic and non-carcinogenic human health risks could be triggered mainly by water consumption as concentrations of arsenic (As), chromium (Cr), nickel (Ni), and lead (Pb) exceeded the upper benchmark of 1 × 10^-4 for adults and children. The results of the carcinogenic risk assessment revealed that children were more vulnerable to health hazards, and quick corrective action is required to control the increased levels of heavy metals at all sample locations. Therefore, through bioaccumulation, human health and the environment are affected in these areas. Using river water for consumption, household work, or even irrigation purposes is not advisable. This study's result highlighted that properly implementing compatible policies and programs is required to improve effluent treatment methods and provide biodegradability to the Dhaleshwari River.

Water quality assessment of Remeți watercourse, Maramureș, Romania, located in a NATURA 2000 protected area subjected to anthropic pressure

The study assessed the evolution of water indicators of Remeți water body that is located in the Remeți locality in the Upper Tisa, a Natura 2000 protected area. Thus, electric conductivity, dissolved oxygen, oxygen saturation, temperature, pH, turbidity, ammonium concentration (NH₄⁺), nitrates (NO₃^-), nitrites (NO₂^-), orthophosphate (PO₄^3-), dissolved Fe, Mn, water hardness, alkalinity (A) and chloride were measured over the January (I)-October (X) 2021 period. This water course was subjected to anthropic pressure, being polluted with nutrients such as ammonium and orthophosphate ions, iron and manganese. The concentrations of other metals were either low (Al, Ba, Li, Ga, Rb, Ni, Sr, Zn, Cu, Ti) or below the detection limit (Pb, Cd). The study was performed over a period of 8 months, namely January 2021-October 2021, covering the 4 seasons, in order to establish their influence on the level of water quality indicators. Exceeded turbidity values and high concentrations of ammonium, orthophosphate and dissolved iron were found, these being generally higher in the summer-autumn months. Dissolved oxygen concentrations were low in the summer-autumn months. Based on the values of the physico-chemical indicators, two types of water quality indices WA-WQI (weighted arithmetic water quality indices) and CCME-WQI (Canadian Council of Ministers of the Environment water quality indices) were calculated to evaluate the global water quality and its evolution over the seasons with a single value. WA-WQI values varied in the range of 78.56-761.63, with a tendency to increase in autumn, showing an intensified tendency of global water quality deterioration due to an increase in ammonium, turbidity, iron and orthophosphates in autumn months while CCME-WQI values were between 39.6 and 68.9, being fair in winter-spring months and marginal / bad in summer and autumn months. The results of this study are advantageous in identifying the level of pollution of Remeți water course, being a signal for local authorities in taking the necessary measures to reduce the pollution around it, for a better human health and conservation of the ecosystems hosted in the protected area.

A holistic framework of water quality evaluation using water quality index (WQI) in the Yihe River (China)

The Yihe River is an important river in Shandong Province, China. It is a catchment river for the South-to-North Water Diversion Project (SNWDP-ER), providing a variety of benefits and ecosystem services, such as flood and drought regulation, fishery and aquaculture, drinking water sources, and biodiversity conservation. In order to objectively reflect the status and changing trend of water environmental quality of the Yihe River, reduce the cost of detection, and improve the efficiency of water quality evaluation, samples were collected at 8 sampling sites in the 220 km main stream of the Yihe River from 2009 to 2019. The spatiotemporal variations of 10 water quality indicators were analyzed, including pH, water temperature (WT), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total phosphorus (TP), ammonia nitrogen (NH3-N), nitrate (NO3-N), fluoride (F-), and sulphate (SO42-). The water quality index (WQI) was used to evaluate the spatiotemporal water quality changes, and the minimum WQI (WQImin) model consisting of five key indicators, i.e., NH3-N, BOD5, DO, SO42-, and WT, was built by using stepwise multiple linear regression analysis. The results indicated that the water quality indicators in the Yihe River showed significant spatiotemporal variations. With the exception of the COD and TP, the other water quality indicators conformed to the Class I or II standards of China, indicating that the water quality of the Yihe River was better than most natural water bodies. Seasonally, the WQI was better in the autumn and higher in the upstream area compared to the downstream. The water quality remained at the "good" level. The weighted WQImin model performed well in evaluating water quality, with coefficient of determination (R2), mean square error (MSE), and percentage error (PE) values of 0.903, 3.05, and 1.70%, respectively.

Robust machine learning algorithms for predicting coastal water quality index

Coastal water quality assessment is an essential task to keep "good water quality" status for living organisms in coastal ecosystems. The Water quality index (WQI) is a widely used tool to assess water quality but this technique has received much criticism due to the model's reliability and inconsistence. The present study used a recently developed improved WQI model for calculating coastal WQIs in Cork Harbour. The aim of the research is to determine the most reliable and robust machine learning (ML) algorithm(s) to anticipate WQIs at each monitoring point instead of repeatedly employing SI and weight values in order to reduce model uncertainty. In this study, we compared eight commonly used algorithms, including Random Forest (RF), Decision Tree (DT), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGB), Extra Tree (ExT), Support Vector Machine (SVM), Linear Regression (LR), and Gaussian Naïve Bayes (GNB). For the purposes of developing the prediction models, the dataset was divided into two groups: training (70%) and testing (30%), whereas the models were validated using the 10-fold cross-validation method. In order to evaluate the models' performance, the RMSE, MSE, MAE, R², and PREI metrics were used in this study. The tree-based DT (RMSE = 0.0, MSE = 0.0, MAE = 0.0, R² = 1.0 and PERI = 0.0) and the ExT (RMSE = 0.0, MSE = 0.0, MAE = 0.0, R² = 1.0 and PERI = 0.0) and ensemble tree-based XGB (RMSE = 0.0, MSE = 0.0, MAE = 0.0, R² = 1.0 and PERI = +0.16 to -0.17) and RF (RMSE = 2.0, MSE = 3.80, MAE = 1.10, R² = 0.98, PERI = +3.52 to -25.38) models outperformed other models. The results of model performance and PREI indicate that the DT, ExT, and GXB models could be effective, robust and significantly reduce model uncertainty in predicting WQIs. The findings of this study are also useful for reducing model uncertainty and optimizing the WQM-WQI model architecture for predicting WQI values.

Comparative assessment of water quality indices-a case study to evaluate water quality for drinking water supply and irrigation in Northern Mexico

Water quality indices (WQIs) are numerical measures used by researchers and water managers to communicate water quality status to the public. This study analyzes the official databases from the CONAGUA monitoring network of the main tributary rivers in the middle basin of the San Pedro-Mezquital River in Durango, Mexico, for a 6-year period (2013-2018). We applied three WQIs to 432 data (18 sampling sites, four samples per year, 6 years): Canadian Council of Ministers of the Environment (CCME) WQI, National Sanitation Foundation (NSF) WQI, and Secretariat of Urban Development and Ecology (SEDUE) WQI. The Canadian index proved to be a flexible, appropriate, and rigorous methodology for assessing water quality based on its use. Results classify the water quality in the studied reservoirs as good, while river water was rated for public use, as marginal to very poor. No statistical significant differences in the quality of water between the rainy (June-October) and dry (November-May) seasons were found. However, tendency shows that in the rainy season the water quality was lower, mainly attributed to agricultural runoffs and bank erosion. The main contamination problem was the presence of fecal coliforms in high concentrations, which is associated to the high population density in the area, low sanitation efficiency, and multiple non-point discharges.

Fluopyram removal from agricultural equipment rinsing water using HSF pilot-scale constructed wetlands

Fluopyram is a novel broad-spectrum fungicide with nematocidal activity, and as an extensively used pesticide, it could cause toxicity in nontarget organisms. The aim of this study was to explore the efficiency of five horizontal subsurface flow (HSF) constructed wetlands (CWs) to remove fluopyram from rinsing water produced during the cleaning of pesticide spraying equipment. Four CWs, namely WG-R, WG-R-P, WG-C, and WG-U, contained fine gravel as porous media. WG-R and WG-R-P were planted with Phragmites australis, WG-C with Typha latifolia, and WG-U was left unplanted. Bioaugmentation with plant growth-promoting rhizobacteria was conducted in WG-R-P unit. The fifth unit (WGZ-R) planted with Phragmites australis and contained gravel and zeolite as porous media. All of CWs were loaded on a daily basis from December 2019 to January 2021 with water fortified with fluopyram. The removal rate follows the pattern of WG-R-P (70.67%) > WGZ-R (62.06%) > WG-C (59.98%) > WG-R (36.10%) > WG-U (25.09%). The most important parameters affecting the fluopyram removal were bioaugmentation, zeolite presence in porous media, and plant species. The WG-R-P unit showed higher fluopyram removal in comparison to the WG-R (increase about 96%), the zeolite increased the fluopyram removal by 72%, and the WG-C unit showed 66% higher fluopyram removal than the WG-R unit.

Competitive exchange between divalent metal ions [Cu(II), Zn(II), Ca(II)] and Hg(II) bound to thiols and natural organic matter

Mercuric Hg(II) ion forms exceptionally strong complexes with various organic ligands, particularly thiols and dissolved organic matter (DOM) in natural water. Few studies, however, have experimentally determined whether or not the presence of base cations and transition metal ions, such as Ca(II), Cu(II), and Zn(II), would compete with Hg(II) bound to these ligands, as concentrations of these metal ions are usually orders of magnitude higher than Hg(II) in aquatic systems. Different from previous model predictions, a significant fraction of Hg(II) bound to cysteine (CYS), glutathione (GSH), or DOM was found to be competitively exchanged by Cu(II), but not by Zn(II) or Ca(II). About 20-75% of CYS-bound-Hg(II) [at 2:1 CYS:Hg(II)] and 14-40% of GSH-bound-Hg(II) [at 1:1 GSH:Hg(II)] were exchanged by Cu(II) at concentrations 1-3 orders of magnitude greater than Hg(II). Competitive exchange was also observed between Cu(II) and Hg(II) bound to DOM, albeit to a lower extent, depending on relative abundances of thiol and carboxylate functional groups on DOM and their equilibrium time with Hg(II). When complexed with ethylenediaminetetraacetate (EDTA), most Hg(II) could be exchanged by Cu(II) and Zn(II), as well as Ca(II) at increasing concentrations. These results shed additional light on competitive exchange reactions between Hg(II) and coexisting metal ions and have important implications in Hg(II) chemical speciation and biogeochemical transformation, particularly in contaminated environments containing relatively high concentrations of Hg(II) and metal ions.

Utility of a source-related matrix in basin management studies: a practice on a sub-Basin in Turkey

According to the water framework directive (WFD), the chemical status should be determined for each water body in a basin through monitoring and evaluation studies, and the gap between the status of water bodies and good water status should be revealed in river basin management plans. In this context, the methodology starting with the evaluation of the monitoring results of the priority substances (PSs) until the end of determining the measures to achieve good condition in surface waters was given in this study. The key aim was to provide a useful methodology defined as a matrix for determining the sources of pollutants that caused this gap. This matrix was applied to the most polluted sub-basin of Küçük Menderes Basin located on the western part of the Turkey. Monitoring studies were carried out in 21 water bodies for a 1-year period for 45 PSs and monitoring results were compared with environmental quality standards (EQS). It was determined that 13 of 45 PSs in 15 water bodies exceeded the EQS. The common PSs in the basin were lead, nickel, fluoranthene, benzo(a)pyrene, C10-13 chloroalkanes, and 4-nonylphenols and average rates of exceeding the EQS were 58.3%, 36.4%, 91.5%, 99.9%, 74.8%, and 49.4%, respectively. The detailed emission inventory of each water body in the basin has been made. Potential sources of PSs were searched via the matrix formed and a total number of 420 basic and supplementary measures were proposed to improve the water quality of the sub-basin.

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.

A comparative study on the performance of NSFWQIm and IRWQIsc in water quality assessment of Sefidroud River in northern Iran

Local water quality indices (WQIs) are usually developed by modifying internationally recognized indices, which are considered reference index. In previous works on WQIs, the performance of local and reference indices has not been compared with each other. Therefore, the question crosses the mind whether using local or international indicators individually can show all qualitative aspects of a water resource. In this study, it was aimed to make this comparison between NSFWQI_m (National Sanitation Foundation Water Quality Index) as the reference index and IRWQI_sc (Iranian Water Quality Index for Surface Water Resource-Conventional Parameters) as the local one through a case study (Sefidroud River in northern Iran). Based on the results, the indices' performance in representing the seasonal and spatial fluctuations of the river water quality was almost similar. However, the water quality scores obtained by the two indices were somewhat different. Based on NSFWQI_m, the average water quality score of the river was about 49.0, by which the water was categorized in "bad" class, while IRWQI_sc represented an average score of 56.1, which corresponds to "fairly good" class. Therefore, NSFWQI_m identified the water quality with stricter criteria than IRWQI_sc, regarding the public health. On the other hand, according to relative standard deviations (0.17 for NSFWQI_m, 0.21 for IRWQI_sc) of the obtained water qualities, IRWQI_sc better distinguished between high and low water qualities of the river. Accordingly, in order to better interpret the quality conditions of surface water resources in Iran, it is necessary to use both indices since NSFWQI_m (reference index) attracts attention to stricter international standards and requirements, while IRWQI_sc (local index) causes more focus on seasons or locations with the worst water quality.