Design of a water quality monitoring network in a large river system using the genetic algorithm

Despite several decades of operations and the increasing importance of water quality monitoring networks, the authorities still rely on experiential insights and subjective judgments in siting water quality monitoring stations. This study proposes an integrated technique which uses a genetic algorithm (GA) and a geographic information system (GIS) for the design of an effective water quality monitoring network in a large river system. In order to develop a design scheme, planning objectives were identified for water quality monitoring networks and corresponding fitness functions were defined using linear combinations of five selection criteria that are critical for developing a monitoring system. The criteria include the representativeness of a river system, compliance with water quality standards, supervision of water use, surveillance of pollution sources and examination of water quality changes. The fitness levels were obtained through a series of calculations of the fitness functions using GIS data. A sensitivity analysis was performed for major parameters such as the numbers of generations, population sizes and probability of crossover and mutation, in order to determine a good fitness level and convergence for optimum solutions. The proposed methodology was applied to the design of water quality monitoring networks in the Nakdong River system, in Korea. The results showed that only 35 out of 110 stations currently in operation coincide with those in the new network design, therefore indicating that the effectiveness of the current monitoring network should be carefully re-examined. From this study, it was concluded that the proposed methodology could be a useful decision support tool for the optimized design of water quality monitoring networks.     

Impact of refined petroleum spills on water quality, macro-invertebrate and microbial communities of a tropical aquatic environment

Water quality characteristics, benthic macro-invertebrates and microbial communities of three first order streams in South West Nigeria were investigated to assess the effects of refined petroleum five months after spillage. All physical and chemical conditions except temperature and pH were significantly different (P<0.01) at the upstream control stations and impacted stations reflecting the perturbational stress. The benthic macro-invertebrate fauna were dominated by arthropods, but the faunal spectrum was dissimilar at all the stations studied. Sampling stations at the epicentre of the spill showed considerable reduction in faunal compositions and relative abundance. Generally, the microbial density and diversity were highest in both soil and water samples from impacted sites than in control sites. There was a significantly higher proportion (P < 0.05) of hydrocarbon utilizers in soil than in water samples in all stations except in samples from stations (P<0.05).     

松花江水质因子分析及动态变化

松花江的水质一直受到各方的关注,尤其是在80年代末到90年代初.大多数的研究都关注重金属、有机有毒污染物等主要污染物的源、汇、归宿以及生态效应.然而,这些研究通常只考虑一个或几个独立的水质指标,多个指标的联合效应则很少研究.文章在监测数据的基础上,对松花江水质运用因子分析方法进行了研究.利用因子分析方法可以综合地考虑每个监测断面上的各个监测指标在不同水文期的变化.分析结果表明,松花江的主要污染物是来自非点源的氮源污染物,且其水质在不同的水文期是不同的.这一结果也表明,因子分析方法在分析水质动态变化上是综合有效的.     

Multiple-pattern parameter identification and uncertainty analysis approach for water quality modeling

This paper presents a multiple-pattern parameter identification and uncertainty analysis approach for robust water quality modeling using a neural network (NN) embedded genetic algorithm (GA). The modeling approach uses an adaptive NN–GA framework to inversely solve the governing equations in a water quality model for multiple parameter patterns, along with an alternating fitness method to maintain solution diversity. The procedure was demonstrated through a coupled 2D hydrodynamic and eutrophication model for Loch Raven Reservoir in Maryland. The inverse problem was formulated as a nonlinear optimization problem minimizing the degree of misfit (DOM) between model results and observed data. A set of NN models was developed to approximate the input-output response relationship of the Loch Raven Reservoir model and was incorporated into a GA framework in an adaptive fashion to search for near-optimal solutions minimizing the DOM. The numerical example showed that the adaptive NN–GA approach is capable of identifying multiple parameter patterns that reproduce the observed data equally well. The resulting parameter patterns were incorporated into the numerical model, and a multiple-pattern robust water quality modeling analysis, along with a compound margin of safety (CMOS) method, was proposed and applied to analyze the parameter pattern uncertainty.     

Chemometrical analysis of waste water monitoring data from Yantra river basin,Bulgaria

A chemometrical study of waste water data is carried out in order to reveal some new information about the pollution events in Yantra river basin, Bulgaria. Cluster analysis shows that no substantial difference in the behaviour of various sites along the river could be found if all chemical pollutants are simultaneously considered as variables (both for direct and indirect inlet of pollutants). Further, the clustering of the variables indicates a separation between organic and nutrition polluting species. The principal components analysis offered information about the latent factors influencing the data structure. In principle, three to four such latent factors explain over 80% of the total variance of the system. These factors are conditionally named “organic pollution”;, “nutrition pollution”; or “natural”; and are slightly different for the cases of direct and indirect inlet.     

Scenario analysis of water pollution control in the typical peri-urban river using a coupled hydrodynamic-water quality model

The water quality pollution and ecological deterioration in peri-urban rivers are usually serious under rapid urbanization and economic growth. In the study, a typical peri-urban river, Nansha River, was selected as a case study to discuss the scheme of peri-urban river rehabilitation. Located in the north part of the Beijing central region, the Nansha River watershed has been designated as an ecologically friendly garden-style area with high-tech industry parks and upscale residential zones. However, the Nansha River is currently seriously contaminated by urban and rural pollutants from both nonpoint sources (NPS) and point sources (PS). In this study, the pollutant loads from point sources and nonpoint sources in the Nansha River watershed were first assessed. A coupled model, derived from the Environmental Fluid Dynamics Code and Water Quality Analysis Simulation Program, was developed to simulate the hydrodynamics and water quality in the Nansha River. According to the characteristics of the typical peri-urban river, three different PS and NPS control scenarios were designed and examined by modeling analyses. Based on the results of the scenario analysis, a river rehabilitation scheme was recommended for implementation.     

Assessment of non-point source pollution using a spatial multicriteria analysis approach

Eutrophication caused by the enrichment of nutrients from diffusing sources is degrading surface water quality throughout the world. Assessing the potential contributions of different land areas in diffuse nutrient export has become an important task in non-point source (NPS) pollution control. Existing methods were often limited by the availability of local data and the complexity of model formulation. This study developed a spatial multicriteria method to evaluate the nitrogen loss potential at the basin level. Four criteria were formulated to characterize the source capacity of nitrogen export, the flow path to water body, the efficiency of runoff generation and the climatic driving force. The proposed method is a low-effort approach since the required data is either already available in a global context or easily produced with limited inputs. Being implemented in GIS environment, this method generates maps that can be easily interpreted to provide decision support. The method was applied to the Huai River Basin, China. The results were validated based on the correlation between the nitrogen loss potential of sub-basin and the water quality class of river. The maps of nitrogen loss potential were helpful for examining the regional pattern of diffuse nitrogen loss, and could facilitate the decisions of NPS pollution management at the provincial or basin level.     

Provision of safe domestic water for the promotion and protection of public health: a case study of the city of Beirut,Lebanon

Securing adequate safe drinking water and proper sanitation is a major challenge facing the developing world. The “Water for Life Decade” emphasizes the importance of upgrading national water quality and sanitation services. This study assessed the domestic water profile in the city of Beirut. Samples were collected from three types of household water sources (municipality, private wells, and vended water bottles) and assessed for their physiochemical and microbiological profile. At the same time, a cross-sectional survey assessing water consumption patterns and the prevalence of water-borne diseases was conducted. The results showed a deficient water quality profile in all three water sources. The measured physiochemical and bacteriological parameters reflected the high frequency of water-borne diseases. Action to secure a safe domestic water supply is essential. The plan should guarantee the protection of water sources, ensure sufficient treatment of domestic water and upgrade the national program for potable water quality control. Periodic quality monitoring and legislating the chaotic water-vending sector are indispensable. Additionally, the deterioration of private well sources by sea and wastewater infiltration necessitates the enforcement of legislation associated with the use and management of private wells. Consumer awareness and active contributions to promote and protect public health are important.     

Optimal locations of monitoring stations in water distribution systems under multiple demand patterns: a flaw of demand coverage method and modification

A flaw of demand coverage method in solving optimal monitoring stations problem under multiple demand patterns was identified in this paper. In the demand coverage method, the demand coverage of each set of monitoring stations is calculated by accumulating their demand coverage under each demand pattern, and the impact of temporal distribution between different time periods or demand patterns is ignored. This could lead to miscalculation of the optimal locations of the monitoring stations. To overcome this flaw, this paper presents a Demand Coverage Index (DCI) based method. The optimization considers extended period unsteady hydraulics due to the change of nodal demands with time. The method is cast in a genetic algorithm framework for integration with Environmental Protection Agency Net (EPANET) and is demonstrated through example applications. Results show that the set of optimal locations of monitoring stations obtained using the DCI method can represent the water quality of water distribution systems under multiple demand patterns better than the one obtained using previous methods.     

Utilization of both benthic macroinvertebrates and physicochemical parameters for evaluating water quality of the stream Cekerek (Tokat, Turkey)

This study examines the applicability of five European biotic indices and the Gammarus:Asellus ratio (G:A), compared with the measurement of physicochemical parameters, in order to determine the water quality at ten sites along the Tokat part of Cekerek stream, in Anatolia, Turkey, during the period February 2002 to January 2003. The biological and chemical results are in good agreement with respect to the water quality. In particular, the G:A ratio was calculated to be high at the first three stations and this result was correlated with the ETBI and the Chandler scores. Consequently, the water quality of Cekerek stream was classified as class I for biological and physicochemical data, except for phosphate, ammonia nitrogen, nitrate and nitrite at the last seven stations. The high concentrations of these chemicals probably result from agricultural runoff and urban sewage. In total, 55 taxa of benthic macroinvertebrates were identified from the Cekerek stream during this study period.     

Strategy for the Control of Land-Based Sources of Marine Pollution in the Wider Caribbean Region

The pollution of the marine environment caused by land-based sources threatens or impairs the health of the ecosystems and the value of human uses of the coastal waters. the Contracting Parties to the Convention for the Protection and Development of the Marine Environment of the Wider Caribbean Region agreed to take all appropriate measures to prevent, reduce and control pollution. in the first meeting of the Contracting Parties, the development of a protocol on the control of marine pollution from land-based sources was recommended as a measure to protect the marine environment.

A small group of experts from the Caribbean Region formulated a strategy for controlling land-based sources of marine pollution. Due to the diverse nature, resources and capabilities of the countries comprising the Region, the pollution control strategy suggested by the group of experts included the following techniques or their most appropriate combination: (1) pollution prevention measures, (2) effluent limitations, (3) water quality limitations, (4) environmental planning, and (5) best management practices. the desirable control strategy should be based on a system of discharge permits in the case of point source pollution, which includes effluent and water quality limitations. the technology based effluent limitations could be applied as a short-range strategy to control pollution from industrial and domestic point source discharges. the use of water quality standards could become part of a long-range strategy for controlling point sources. for nonpoint sources, it would be virtually impossible to develop effluent limitations. Thus, the implementation of best management practices and effective environmental planning would be the most reasonable control strategy for non-point sources. However, pollution prevention measures could consist of a “black list” of substances that should be completely banned, and a “grey list” for those that should be strictly limited. These lists should be adopted or appropriately modified for the conditions of the Wider Caribbean Region.

The development of control based on the water quality of the receiving body of water involves the collection and analysis of effluent and ambient data to develop water quality based permit limits and to assess compliance with these permits. Finally, any marine pollution control strategy developed by the countries of the Region should be mutually agreed upon and implemented within a period of ten years from the ratification of a protocol on land-based sources of marine pollution.     

Source identification and prediction of nitrogen and phosphorus pollution of Lake Taihu by an ensemble machine learning technique

● A machine learning model was used to identify lake nutrient pollution sources. ● XGBoost model showed the best performance for lake water quality prediction. ● Model feature size was reduced by screening the key features with the MIC method. ● TN and TP concentrations of Lake Taihu are mainly affected by endogenous sources. ● Next-month lake TN and TP concentrations were predicted accurately. Effective control of lake eutrophication necessitates a full understanding of the complicated nitrogen and phosphorus pollution sources, for which mathematical modeling is commonly adopted. In contrast to the conventional knowledge-based models that usually perform poorly due to insufficient knowledge of pollutant geochemical cycling, we employed an ensemble machine learning (ML) model to identify the key nitrogen and phosphorus sources of lakes. Six ML models were developed based on 13 years of historical data of Lake Taihu’s water quality, environmental input, and meteorological conditions, among which the XGBoost model stood out as the best model for total nitrogen (TN) and total phosphorus (TP) prediction. The results suggest that the lake TN is mainly affected by the endogenous load and inflow river water quality, while the lake TP is predominantly from endogenous sources. The prediction of the lake TN and TP concentration changes in response to these key feature variations suggests that endogenous source control is a highly desirable option for lake eutrophication control. Finally, one-month-ahead prediction of lake TN and TP concentrations (R² of 0.85 and 0.95, respectively) was achieved based on this model with sliding time window lengths of 9 and 6 months, respectively. Our work demonstrates the great potential of using ensemble ML models for lake pollution source tracking and prediction, which may provide valuable references for early warning and rational control of lake eutrophication.     

Assessment of temporal and spatial variations in water quality using multivariate statistical methods： a case study of the Xin＇anjiang River,China

This study evaluated the temporal and spatial variations of water quality data sets for the Xin＇anjiang River through the use of multivariate statistical techniques, including cluster analysis （CA）, discriminant analysis （DA）, correlation analysis, and principal component analysis （PCA）. The water samples, measured by ten parameters, were collected every month for three years （2008-2010） from eight sampling stations located along the river. The hierarchical CA classified the 12 months into three periods （First, Second and Third Period） and the eight sampling sites into three groups （Groups 1, 2 and 3） based on seasonal differences and various pollution levels caused by physicochemical properties and anthropogenic activ- ities. DA identified three significant parameters （tempera- ture, pH and E.coli） to distinguish temporal groups with close to 76% correct assignment. The DA also discovered five parameters （temperature, electricity conductivity, total nitrogen, chemical oxygen demand and total phosphorus） for spatial variation analysis, with 80.56% correct assignment. The non-parametric correlation coefficient （Spear- man R） explained the relationship between the water quality parameters and the basin characteristics, and the GIS made the results visual and direct. The PCA identified four PCs for Groups 1 and 2, and three PCs for Group 3. These PCs captured 68.94%, 67.48% and 70.35% of the total variance of Groups 1, 2 and 3, respectively. Although natural pollution affects the Xin＇anjiang River, the main sources of pollution included agricultural activities, industrial waste, and domestic wastewater.     

Macrobenthic subtidal communities in relation to sediment pollution: the phylum-level meta-analysis approach in a south-eastern coastal region of South America

The relationships between macrobenthic subtidal community structure and the status of sediment pollution were analysed at 24 sampling stations in the Montevideo coastal zone. In order to judge the status of community perturbation a phylum-level meta-analysis was applied to the production data from the Montevideo coastal zone samples alone and combined with the original training data set from 50 samples collected on the NE European shelf. The community was dominated by the gastropod Heleobia cf. australis. The MDS (multi-dimensional scaling) ordination with abundance data (species-level) and the MDS ordination with production data (phylum level), using only our samples, showed the formation of three groups of stations. Results of the BIO-ENV procedure showed that lead, salinity and polycyclic aromatic hydrocarbons (PAHs) were the variables that best explained the biological pattern observed. However, a clear salinity gradient was observed from the inner stations of Montevideo Bay to the outer coastal stations; the high levels of Pb, PAH and Cr concentrations recorded at stations B, C and D in Montevideo Bay were important in discriminating these locations from the others. The MDS ordination combining the production data from the 24 samples from the Montevideo coastal zone with the original data set showed correct assessment of the pollution status for the 24 samples from Montevideo on a common scale of perturbation. The separation of the Montevideo coastal zone samples seems to be mainly due to the high proportion of molluscs. Our results suggest general applicability of the phylum-level meta-analysis approach, even in such cases as this, with high dominance of only one phylum; however, more studies are still necessary.Communicated by O. Kinne, Oldendorf/Luhe     

Southwest monsoon influences the water quality and waste assimilative capacity in the Mandovi estuary (Goa state,India)

The monsoon-dominated Mandovi estuary is located in Goa state – a global tourist destination along the centralwest coast of India. In addition to factor analyses of water quality data, the water quality index (WQI), trophic state index (TSI) and percentage of freshwater volume in the estuary are calculated in order to infer the general waste assimilative capacity and prevailing water quality conditions. Factor analysis showed a dominance of PO₄–P, NO₂–N, NH₃–N, total suspended solids (TSS) and turbidity during southwest (SW) monsoon relative to other seasons. The WQI suggested that an increase in nutrients, turbidity and TSS during SW monsoon increase the WQI values beyond 2, rendering the water at some locations slightly polluted. During pre-monsoon, considerable increase in the WQI is observed at all the upstream stations rendering slightly polluted water at these stations. The TSI showed an average value of 46.95 during SW monsoon, 42.43 during post-monsoon and 48.42 during the pre-monsoon seasons, suggesting better productivity level during pre-monsoon, followed by SW monsoon, but the least during the post-monsoon. All the seasons, however, indicated a mesotrophic condition in the estuary and the assimilative capacity of the estuary is found to be in good to fairly good state (pre-monsoon?相似文献   

长江上游宜宾至泸州江段突发水污染风险评估

为防控长江上游重大突发水污染事件的发生,收集整理长江宜宾至泸州江段沿江水环境污染源及受体基础资料,构建水环境潜在污染风险分级评价体系。采用地统计学理论和地理信息系统(Geographic Information System,GIS)相结合的方法开展突发水污染风险分区评价研究,以揭示研究区江段突发水污染风险空间分布差异性。结果表明,污染源或受体热点分布主要集中在城镇化、工业化较快的地区,如宜宾市叙州区污染源最多,泸州市龙马潭区高风险污染源最密集,宜宾县和南溪县高敏感受体数量最多;其他区域污染源或受体分布较为均衡,未形成明显的冷点区域。水环境潜在污染高风险区集中分布在龙马潭区江段和江阳区江段,须提高该区域对潜在污染的风险管理能力,以降低污染事故发生的可能性。     

A modeling system for drinking water sources and its application to Jiangdong Reservoir in Xiamen city

Drinking water sources are highly valued by authorities for safeguarding the life of a city. Models are widely applied as important and effective tools in the management of water sources. However, it is difficult to apply models in water source management because water managers are often not equipped with the professional knowledge and operational skills necessary for making use of the models. This paper introduces a drinking water source simulation and prediction system that consists of a watershed model, a hydrological model and a water quality model. This system provides methods and technical guidance for the conventional management of water sources and emergency water event response. In this study, the sub-models of the system were developed based on the data of the Jiangdong Reservoir in Xiamen, and the model validation was based on local monitoring data. The hydrological model and water quality model were integrated by computer programming, and the watershed model was indirectly integrated into the system through a network platform. Furthermore, three applications for Jiangdong Reservoir water protection utilizing the system were introduced in this paper, including a conventional simulation, an emergency simulation, and an emergency measures evaluation.     

Watershed land use effects on lake water quality in Denmark

Mitigating nutrient losses from anthropogenic nonpoint sources is today of particular importance for improving the water quality of numerous freshwater lakes worldwide. Several empirical relationships between land use and in-lake water quality variables have been developed, but they are often weak, which can in part be attributed to lack of detailed information about land use activities or point sources. We examined a comprehensive data set comprising land use data, point-source information, and in-lake water quality for 414 Danish lakes. By excluding point-source-influenced lakes (n = 210), the strength in relationship (R2) between in-lake total nitrogen (TN) and total phosphorus (TP) concentrations and the proportion of agricultural land use in the watershed increased markedly, from 10-12% to 39-42% for deep lakes and from 10-12% to 21-23% for shallow lakes, with the highest increase for TN. Relationships between TP and agricultural land use were even stronger for lakes with rivers in their watershed (55%) compared to lakes without (28%), indicating that rivers mediate a stronger linkage between landscape activity and lake water quality by providing a "delivery" mechanism for excess nutrients in the watershed. When examining the effect of different near-freshwater land zones in contrast to the entire watershed, relationships generally improved with size of zone (25, 50, 100, 200, and 400 m from the edge of lake and streams) but were by far strongest using the entire watershed. The proportion of agricultural land use in the entire watershed was best in explaining lake water quality, both relative to estimated nutrient surplus at agricultural field level and near-lake land use, which somewhat contrasts typical strategies of management policies that mainly target agricultural nutrient applications and implementation of near-water buffer zones. This study suggests that transport mechanisms within the whole catchment are important for the nutrient export to lakes. Hence, the whole watershed should be considered when managing nutrient loadings to lakes, and future policies should ideally target measures that reduce the proportion of cultivated land in the watershed to successfully improve lake water quality.     

Trace metals accumulation in soil irrigated with polluted water and assessment of human health risk from vegetable consumption in Bangladesh

Trace metals accumulation in soil irrigated with polluted water and human health risk from vegetable consumption was assessed based on the data available in the literature on metals pollution of water, soil, sediment and vegetables from the cites of Bangladesh. The quantitative data on metal concentrations, their contamination levels and their pollution sources have not been systematically gathered and studied so far. The data on metal concentrations, sources, contamination levels, sample collection and analytical tools used were collected, compared and discussed. The USEPA-recommended method for health risk assessment was used to estimate human risk from vegetable consumption. Concentrations of metals in water were highly variable, and the mean concentrations of Cd, Cr, Cu and As in water were found to be higher than the FAO irrigation water quality standard. In most cases, mean concentrations of metals in soil were higher than the Bangladesh background value. Based on geoaccumulation index (I _geo) values, soils of Dhaka city are considered as highly contaminated. The I _geo shows Cd, As, Cu, Ni, Pb and Cr contamination of agricultural soils and sediments of the cities all over the Bangladesh. Polluted water irrigation and agrochemicals are identified as dominant sources of metals in agricultural soils. Vegetable contamination by metals poses both non-carcinogenic and carcinogenic risks to the public. Based on the results of the pollution and health risk assessments, Cd, As, Cr, Cu, Pb and Ni are identified as the priority control metals and the Dhaka city is recommended as the priority control city. This study provides quantitative evidence demonstrating the critical need for strengthened wastewater discharge regulations in order to protect residents from heavy metal discharges into the environment.     

Chemometrical classification of biomonitoring analytical data for heavy metals part I. trees (leaves) as bioindicators

The application of tree species (leaves) as biomonitoring devices is studies by the use of cluster analysis. It is shown that the chemical analysis of leaf samples should be accompanied by a careful chemometrical data treatment in order to obtain a reliable information on the behaviour of various tree species to heavy metal exposure (8 trees for three heavy metals in twelve different places) in fall and spring season. Additionally, the distribution of the sampling sites is studied by the same approach and a commentary on the urban aspects of sampling is given.