Local Water Quality Research Articles

Evaluation of water quality reliability based on entropy in water distribution system

In this paper, water quality redundancy/reliability was proposed based on information entropy technology including Tsalli entropy and Shannon entropy in water distribution system (WDS), which was applied to 26 WDS with various layouts. The residual chlorine is considered to be representative of water quality parameter, comply with first-order decay model. The method was performed based on EPANET toolkit and MATLAB environment. The results indicated that approach 1 focused on local nodal water quality is more suitable for evaluating water quality reliability, especially for small WDS. The water quality redundancy increased with the loop number for various layouts, and has an exponential relationship with distance-weighted average nodal degree. The water quality redundancy has a linear relationship with the hydraulic redundancy. In addition, the water quality reliability based on Tsalli entropy and Shannon entropy decreased with the value of decay coefficient, which indicated that the water quality redundancy/reliability can be applied to evaluate and compare the reliability of WDS from view of water quality. The proposed evaluation method based on information entropy can help design, analyze, and improve the scenarios in WDS.

Long-Term Effects of the Harvesting of Trapa natans on Local Water Quality and Aquatic Macrophyte Community in Lake Erhai, China

Trapanatansis one of the main species causing the swamping in the littoral zones of Erhai Lake. It commonly forms a dense canopy on the water surface in the growing season (June–September), which hampers the local water quality and habitat of submerged macrophytes, and releases nutrients to the water after death in autumn and winter, resulting in the deterioration of local water quality. At present, there are many and positive research studies on the short-term effects of harvesting water chestnut on water quality and aquatic plants, but long-term observation results are lacking. In response to the above problems, we studied responses of water quality and aquatic plant community to the removal ofTrapain littoral zone of a northern bay in Erhai from August 2014 to January 2017. This could be the first attempt to discover the long-term effects of floating-leaved vegetation management in the freshwater ecosystem. The results showed that the artificial removal ofTrapasignificantly improved the local water quality in the growing season, for example, the concentrations of total nitrogen (TN), dissolved nitrogen (DN), total phosphorus (TP), and dissolved phosphorus (DP) in the non-Trapazone (NTZ) were much lower than the concentrations of those in the adjacentTrapazone (TZ). And the biomass of aquatic macrophyte community (BAMC) was significantly increased in the NTZ, up to the maximum value of about 21 kg/m2in fresh weight. However, the diversity indexes of the community in the NTZ declined. Therefore, we suggested that although the removal ofTrapaimproved the water quality and increased the productivity of the submerged aquatic plant community, it reduced the species diversity of the aquatic plant community in the long run. This is another issue that we need to pay attention to in the later management in Erhai Lake.

How Hercules cleans up the Augean stables: differentiated implementation of the EU Water Framework Directive

AbstractRealising the goals of the European Union (EU) Water Framework Directive is difficult. The differentiation of water policies according to local conditions enjoys increasing attention and may be necessary to achieve good ecological status in all European waters. This paper seeks to explore to what extent and how local water quality determines the degree of coercion, i.e. the extent to which differentiated policies are voluntary or rather imposed upon policy addressees, of spatially differentiated water policies. It does so on the basis of seven cases in five EU Member States. For highly polluted waters, spatially differentiated policies tend either to make the use of authoritative policy instruments, i.e. coercion by way of formal regulation, or to rely on the threat to introduce such regulation. For preventing the deterioration of relatively ‘clean’ waters, voluntary instruments based on information and persuasion dominate, often supported by subsidies and/or the direct input of public resources. In relation to the spatial differentiation of water policies, issues of data demand, equality and legitimacy have to be taken into account.

Coliformes totais e fecais em águas da rede pública da comuna do Forte Santa Rita

The present study addresses the presence of totals and fecal coliforms in the water consumed by the population of Forte Santa Rita Commune, Municipal district of Moçâmedes in Angola, to allow comparing its actual state with the pattern values established by WHO, allowing taking the appropriate measure so that it is provided with the required quality. The objective of the study was to evaluate the microbiological quality of the water consumed by the population of Forte Santa Rita Commune, in order to facilitate future corrective and preventive actions. It was evaluated the microbiological quality of consumed water in 5 points of Forte Santa Rita Commune, which were analyzed at the local water quality control laboratory in Huila. This was a study with a quantitative and qualitative focus, in which was used filtrate membrane technique. As a result, when analyzing the 5 water samples in October 2019, the presence of Escherichia coli colonies was found in 2 samples, corresponding to 40% of water samples analyzed, whereas in December, the collected samples showed absence of totals and fecal coliforms in 100% of the analyzed samples, it demonstrates an improvement in the water quality for the human consumption. It was concluded that, although the December water samples shows absence of totals and fecal coliforms, it cannot be discarded the need of a continued surveillance through tests, proving its quality.

Users’ Perceptions of Local Public Water and Waste Services: A Case Study for Sustainable Development

Access to safe drinking water is essential to good health, a basic human right, and a component of effective policy for health protection. Improving the quality of local public water and waste services is one of the United Nations Sustainable Development Goals (Goal 6: Clean Water and Sanitation). This study aims to know the degree of satisfaction of domestic users who receive services related to water and waste in municipalities with less than 20,000 inhabitants in the province of Badajoz (Spain). We carry out this research because the perception of municipal services provided by the public administration is usually negative and deficient. The case study PROMEDIO, the consortium formula, is described as a successful partnership to improve the quality of local public water and waste services. For this purpose, a detailed analysis of the different aspects involved in the relationship between the users and the services provided is carried out. The consortium was found to increase citizens’ satisfaction with the services provided, given the close relationship between the municipality and the users.

Bacteriome depiction and the trophic status of the largest Northern highland lake from Andes system: Lago de Tota, Boyacá, Colombia.

Lago de Tota is the largest highland lake in Colombia and one of the most remarkable of Northern Andean Mountain range. This lake is under an anthropogenic-based eutrophication process as a consequence of non-sustainable agriculture practices developing nearby. Notable relationship between the trophic status and Bacteriome loop dynamics has been increasingly disclosed in lakes worldwide. We performed a 16S sequencing analysis to depict the bacterial community present and we inferred its potential gene function in Lago de Tota. Parameters for determining current trophic condition such as total nitrogen (TN), dissolved carbon (DOC), particulate organic matter (POM), and chlorophyll-a (chl-a) were measured. A total of 440 Operational Taxonomic Units (OTUs) arranged into 50 classes were identified based on V3-V4 regions of the 16S rRNA gene, harboring high-frequent likely found environmental classes such as Actinobacteria, Gammaproteobacteria, Bacteroidia, Acidimicrobia, and Verrucomicrobiae. A total of 26 bacterial classes configure most abundant predicted functional processes involved in organic matter decomposition (i.e., carbohydrate metabolism, amino acid metabolism, xenobiotic biodegradation, and energy metabolism). In general, Actinobacteria, Alphaproteobacteria, and Gammaproteobacteria show the highest potential gene functional contributors, although other low-frequent classes OTUs are also relevant in processes of carbohydrate metabolism, xenobiotic biodegradation, and energy metabolism. The Trophic State Index indicates an oligo-mesotrophic status, and additional variables measured (i.e., POM, DOC) suggest the increasing carbon accumulation. Results provide preliminary evidence for several bacteria groups related to eutrophication of Lago de Tota. Under this picture, we suggest that further studies for Bacteriome loop spatial-temporal description are essential to inform local water quality monitoring strategies.

Protecting local water quality has global benefits

Surface water is among Earth’s most important resources. Yet, benefit–cost studies often report that the costs of water quality protection exceed its benefits. One possible reason for this seeming paradox is that often only a narrow range of local water quality benefits are considered. In particular, the climate damages from water pollution have rarely been quantified. Recent advances in global water science allow the computation of the global methane emission from lakes caused by human nutrient enrichment (eutrophication). Here, we estimate the present value of the global social cost of eutrophication-driven methane emissions from lakes between 2015 and 2050 to be $7.5–$81 trillion (2015 $US), and in a case-study for one well-studied lake (Lake Erie) we find the global value of avoiding eutrophication exceeds local values of either beach use or sport fishing by 10-fold.

Water Quality Monitoring System for Water Distribution Project in Jiaxing, Zhejiang Province

In the construction of water distribution pipeline system in Jiaxing City, in order to monitor the water quality and water environment, a continuous observation network is constructed according to the existing technical specifications. At present, the system runs well and produces continuous monitoring data, which provides basis for local water quality protection.

Assessment of Groundwater Quality for Drinking and Domestic Purposes through Local Survey and Water Quality Index in Vietnam

The quality of groundwater resources is increasingly declining, significantly affecting people’s life and health. The study aims to assess public perception on existing groundwater quality and scheme over conventionally used free groundwater. The contemporaneous analytical procedures applied to determine the concentration of physical parameters: total dissolved solids and total solids and chemical parameters: pH, nitrite (N-NO2-), nitrate (N- NO3-), ammonium (N-NH4+/ NH3), iron (FeII + III) and total hardness were collected for 30 drinking water well samples located in 5 Quarters (An Hoa, An Loi, Ben Don, Phu Hoa, and Phu Nghi) to calculate the water quality index. The results show that up to 96% of people still use groundwater as their main source of drinking, domestic purposes, although groundwater quality is showing a serious decline in quality. The low pH index ranges from 3.0 ÷ 4.5. On average, 3.5 ÷ 4.0 pH of groundwater samples are outside the permissible limit according to VN standards 09: 2015 (5.5 - 8.5), which makes the water acidic, which harmful to human health. Besides, 10% of groundwater samples had high nitrate content, and 6.67% of water samples had ammonium content that did not meet VN standards 09: 2015. The current state of groundwater quality is not good for cooking and drinking. The results will benefit future groundwater exploitation to support more evidence of water quality and deteriorate the water quality soon, ultimately proving to be disastrous for all living beings in the region.

Local Water Quality, Diarrheal Disease, and the Unintended Consequences of Soda Taxes

Abstract Could taxing sugar-sweetened beverages in areas where clean water is unavailable lead to increases in diarrheal disease? An excise tax introduced in Mexico in 2014 led to a significant 6.6 percent increase in gastrointestinal disease rates in areas lacking safe drinking water throughout the first year of the tax, with evidence of a diminishing impact in the second year. Suggestive evidence of a differential increase in the consumption of bottled water by households without access to safe water two years post-tax provides a potential explanation for this declining pattern. The costs implied by these results are small, particularly compared to tax revenues and the potential public health benefits. However, these findings inform the need for accompanying soda taxes with policy interventions that guarantee safe drinking water for vulnerable populations.

Rainfall prediction using optimally pruned extreme learning machines

Rainfall impacts local water quantity and quality. Accurate and timely prediction of rainfall is highly desirable in water management and hydrogeologic hazards mitigation, which is critical for the environmentally sustainable development. Previous rainfall prediction processes are complex and computationally costly for its intrinsic high uncertainty and variability. In this paper, a data-driven approach is applied to predict the rainfall based on historic data via time-series modeling and optimally pruned extreme learning machine (OP-ELM). The rainfall datasets collected from six counties within Three Georges Reservoir are utilized as case studies in this research, first, the rainfall data is pre-processed with outlier removal and missing value imputation, and the monthly ahead difference is computed based on the instant average of monthly rainfall. Next, the autocorrelation function and partial autocorrelation function were computed and the Ljung–Box test statistic is utilized to explore the significance of the historic lagged-series. All the statistically significant historic lags are selected as inputs for prediction algorithms. Last, an OP-ELM algorithm is developed to predict the monthly rainfall with tenfold cross validation. Four activation functions: the sigmoid, sine, hardlim, and radial basis function, are considered in the OP-ELM. The prediction performance is evaluated with metrics including mean absolute error, mean absolute percentage error, root mean square error, and max error rate. Overall, the computational results indicate the proposed framework outperforms the other benchmarking machine learning algorithms through six case studies in Three Gorges Reservoir, China.

Groundwater contamination in the Gulf Cooperation Council (GCC) countries: a review.

Groundwater quality levels are currently deteriorating in Gulf Cooperation Council (GCC) countries due to excessive surface and subsurface human activities. Agricultural and industrial activities, landfill seepage and seawater intrusion have been attributed to the deterioration of groundwater quality in GCC states. Such a deterioration of groundwater quality could affect water security in the region, including human health and the ecosystem. Therefore, this review aims to identify the key causes of groundwater contamination across the GCC countries from the published literature. In addition, the review summarizes the major components of the groundwater contaminants across the GCC countries. The results have shown that heavy metals, several cations and anions are the leading cause of groundwater pollution. In most cases, the level of metals and ion contaminants exceeds both the local and international water quality standards. The results have observed the presence of high levels of coliform and radioactive elements in groundwater, especially Uranium and Radium, thereby posing additional risk to human health through consumption. Considering the scarcity of freshwater resources in GCC, urgent actions are required from the decision-makers and relevant regulatory bodies to set up and implement long-term mitigation strategies and stringent policies that will protect the groundwater resources from the adverse effects of anthropogenic activities.

Improving the resolution of UAV-based remote sensing data of water quality of Lake Hachiroko, Japan by neural networks

Remote sensing techniques for periodically collecting global data have been widely used for water quality monitoring. Satellites with a ground resolution of 10 to 30 m obtain information over broad areas, making it difficult to use them to evaluate local water quality. Methods for improving satellite data resolution allow for water quality monitoring over both wide and local areas. However, previous studies have failed to target water bodies that undergo drastic changes; moreover, they have not sufficiently examined features contributing to resolution improvement. This study proposes a resolution improvement method using a neural network, which performs learning so that the output matches the high-resolution data when the target pixel and its surrounding pixels in the low-resolution data are input. Moreover, the band ratio of data obtained from an unmanned aerial vehicle was used in the learning process as an input feature. We investigated the (i) band ratio providing highly accurate resolution improvement and (ii) application of a new resolution improvement method to the estimation of suspended solid conditions for water quality parameters. Finally, the proposed method was compared with the bicubic method for validation. The results indicate that the estimated map at the band ratio B/R in the resolution improvement data created via the proposed method can be used to greatly improve the resolution in areas with high levels of suspended solids, compared to the water quality estimation maps created using the bicubic method.

Metagenomic Sequencing and Quantitative Real-Time PCR for Fecal Pollution Assessment in an Urban Watershed.

Microbial contamination of recreation waters is a major concern globally, with pollutants originating from many sources, including human and other animal wastes often introduced during storm events. Fecal contamination is traditionally monitored by employing culture methods targeting fecal indicator bacteria (FIB), namely E. coli and enterococci, which provides only limited information of a few microbial taxa and no information on their sources. Host-associated qPCR and metagenomic DNA sequencing are complementary methods for FIB monitoring that can provide enhanced understanding of microbial communities and sources of fecal pollution. Whole metagenome sequencing (WMS), quantitative real-time PCR (qPCR), and culture-based FIB tests were performed in an urban watershed before and after a rainfall event to determine the feasibility and application of employing a multi-assay approach for examining microbial content of ambient source waters. Cultivated E. coli and enterococci enumeration confirmed presence of fecal contamination in all samples exceeding local single sample recreational water quality thresholds (E. coli, 410 MPN/100 mL; enterococci, 107 MPN/100 mL) following a rainfall. Test results obtained with qPCR showed concentrations of E. coli, enterococci, and human-associated genetic markers increased after rainfall by 1.52-, 1.26-, and 1.11-fold log10 copies per 100 mL, respectively. Taxonomic analysis of the surface water microbiome and detection of antibiotic resistance genes, general FIB, and human-associated microorganisms were also employed. Results showed that fecal contamination from multiple sources (human, avian, dog, and ruminant), as well as FIB, enteric microorganisms, and antibiotic resistance genes increased demonstrably after a storm event. In summary, the addition of qPCR and WMS to traditional surrogate techniques may provide enhanced characterization and improved understanding of microbial pollution sources in ambient waters.

Localized Water Quality Improvement in the Choptank Estuary, a Tributary of Chesapeake Bay

Chesapeake Bay has a long history of nutrient pollution resulting in degraded water quality. However, we report improvements in chlorophyll a in surface waters and dissolved oxygen in bottom waters at one of three estuarine stations in the Choptank tributary of Chesapeake Bay. We updated a previous nutrient budget for the estuary constructed for reference year 1998 using rates of atmospheric deposition, inputs of watershed diffuse sources (primarily agriculture), and discharges of point sources (primarily human waste) for reference year 2017. Parallel trends suggest that improvements in water quality at the one station were likely due to 20% reductions in direct atmospheric deposition on the estuary’s surface and 78–95% reductions in wastewater N and P due to installation of tertiary treatment. The agricultural sector, the dominant source of N and P, appeared to provide little contribution to improved water quality during this period. Although efforts to reduce nutrient losses from agriculture are common throughout the Choptank basin, widespread reductions from agricultural diffuse sources could make large contributions to improved water quality at all stations in the estuary. The response in the Choptank is similar to those observed elsewhere in the USA, Europe, Australia, and New Zealand due to improved wastewater treatment. Similar to our findings, the upper Potomac River of Chesapeake Bay saw improvements driven by reductions in atmospheric deposition. Unfortunately, few studies elsewhere have shown improvements in water quality due to agricultural management. The data presented here indicate that public and industrial investments in reductions of atmospheric emissions and upgrades to wastewater treatment plants have improved estuarine water quality in the Choptank.

Consider the Hidden Costs of PFAS Treatment

Water utilities dealing with PFAS need to understand local water quality conditions, available technologies, regulatory drivers, and public engagement while they pursue proactive planning and weigh treatment costs.

Adopting cover crops and buffer strips to reduce nonpoint source pollution: Understanding farmers’ perspectives in the US Northern Great Plains

Agricultural nonpoint source pollution has been identified as a major cause of water quality impairments. Utilizing survey data from the Northern Great Plains, this paper provides a better understanding of farmers’ perceptions on water quality issues in their local areas. Excessive algal bloom and aquatic plants were among producers’ top water quality concerns in North Dakota, South Dakota, and Nebraska. Fertilizers/pesticides were perceived as either not a problem (28.7%) or a slight problem (43.7%) when it comes to the water pollution sources. While only 17.2% of the respondents indicated agreement upon paying taxes to help protect the local water quality, 43.5% agreed to implement conservation practices (CPs) at some cost, and 70.1% agreed to implement CPs at no direct cost to farmers to improve water quality. This paper examined the factors associated with the adoption of cover crops and buffer strips. We found that producers’ adoption decisions of cover crops largely hinged on farm characteristics and management variables, such as land ownership, farm size, livestock ownership, and adoption status of other farm management practices, while water quality information and producer perceptions affected the adoption decisions of both cover crops and buffer strips. To further promote CP adoption and reduce water pollution, our results highlighted the importance of both monetary incentives and outreach efforts that disseminate information on water pollution status and pollution sources, as well as technical support on CPs suitable for the farm.

Concentrations of Poorly Studied Technology-Critical Elements Ge, Zr, Mo, Sn, Sb, Hf, Ta, W and Ti in the Sediments of Three Northern Egyptian Lakes

Thirty five Sediment samples were collected from three Northern Egyptian Lakes namely El Burullus, El Manzala and El Bardawil to evaluate for the first time the concentrations of poorly studied technology-critical elements, namely Ge, Zr, Mo, Sn, Sb, Hf, Ta, W and Ti, and how that may be linked to local water quality parameters and other geochemical factors. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was used to determine element’s concentration. The results were compared with Upper Continental Crust (UCC) and Nile sediment (ANS). Lake sediments generally have relatively low contents of most elements. The average concentration of Zr, Hf, Ta and W are lower than UCC and ANS in three Lakes. El Bardawil Lake attained the lowest average concentration for all elements except Mo. Correlation analysis revealed that water quality and geochemical properties did not play any important role affecting the metal distribution and the studied metals are generally not affected by the complex lacustrine system of these lakes and their spatial distribution still not affected by the different anthropogenic activates.

Using LSTM Neural Network Based on Improved PSO and Attention Mechanism for Predicting the Effluent COD in a Wastewater Treatment Plant

Enhancing the monitoring capabilities of wastewater treatment plant (WWTP) key features can accomplish accurate prediction to help WWTPs develop a plan, which is of great significance to control regional water environmental pollution. Chemical oxygen demand (COD) is one of the key features of wastewater treatment. Traditional monitoring methods are time consuming and have high costs making it difficult to meet the needs of rapid monitoring in practical applications. To address this issue, a method for optimizing a long short term memory (LSTM) neural network model based on adaptive hybrid mutation particle swarm optimization (AHMPSO) and an attention mechanism (AM) is proposed. As the hyperparameters of the LSTM are difficult to select, AHMPSO is used to optimize the LSTM. A nonlinear variable inertia weight with random factors is introduced to balance the global search ability and the local search ability and to improve the convergence speed of the PSO algorithm. In addition, the hybrid mutation strategy is added in the search process to reduce the risk of particles falling into local optimal solutions. Finally, an AM is added to the LSTM model to mine local water quality features to improve the effluent COD prediction accuracy. Compared with other models (LSTM, LSTM-AM, and PSO-LSTM-AM), the RMSE(the root mean square error) of the optimized model decreased by 7.803%-19.499%, the MAE(the mean absolute error) of the optimized model decreased by 9.669%-27.551%, the MAPE(the mean absolute error) of the optimized model decreased by 8.993%-25.996%, and the R2 (the coefficient of determination) value of the optimized model increased by 3.313%-11.229%. The experimental results show that the optimized model has better performance and achieves a more accurate prediction of the effluent COD.

Identifying causes of poor water quality in a Polish agricultural catchment for designing effective and targeted mitigation measures

The Gowienica Miedwiańska catchment is a small agricultural catchment located in the NW of Poland draining into Lake Miedwie, on which a drinking water source for the city of Szczecin is located. The catchment is characterized by very rich soils. Subsequently, agriculture is intensive and this is thought to influence the poor water quality in the local area. Despite more than 20 years since first programmes of measures towards protection of water quality have been introduced into the catchment, these have not been produced the expected results, and the local farming community cites other sources such as poor sewage management rather that agricultural activity, as responsible for this problem. Evaluation of flow pathways in the catchment and identification of the areas responsible for the highest impact on local water quality was therefore conducted within the EU funded project Waterprotect. The aim of this study was to clarify sources of pollution precisely in space and time, in order to increase trust from stakeholders, so that targeted measures can be used effectively to improve water quality. The study included water quality monitoring, isotopic analysis and numerical flow modelling. Results showed that water quality in the catchment is spatially and temporally variable. 93% of nitrogen loadings into the Miedwie lake have been attributed to agriculture and only 7% to wastewater inputs. The local hydrology and hydrogeology play an important role in the distribution of the impacts from these inputs. As a result, three sub-catchments were identified which are differentiated by dominant pollution source, land use, and hydraulic characteristics. The highest inputs from agriculture have been identified in the most upper sub-catchment and this area have been pointed out as most suitable for implementation of agricultural best management practices towards protection of water quality at a local level.