Evaluation of water quality index for drinking purposes for river Netravathi, Mangalore, South India

An attempt has been made to develop water quality index (WQI), using six water quality parameters Dissolved oxygen (DO), Biochemical oxygen Demand (BOD), Most Probable Number (MPN), Turbidity, Total Dissolved Solids (TDS) and pH measured at eight different stations along the river basin. Rating curves were drawn based on the tolerance limits of inland waters and health point of view. Bhargava WQI method and Harmonic Mean WQI method were used to find overall WQI along the stretch of the river basin. Five point rating scale was used to classify water quality in each of the study areas. It was found that the water quality of Netravathi varied from Excellent to Marginal range by Bhargava WQI method and Excellent to Poor range by Harmonic Mean WQI method. It was observed that the impact of human activity was severe on most of the parameters. The MPN values exceeded the tolerable limits at almost all the stations. It was observed that the main cause of deterioration in water quality was due to the lack of proper sanitation, unprotected river sites and high anthropogenic activities.     

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin,Brazil

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008–2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.     

Assessment of surface water quality using a growing hierarchical self-organizing map: a case study of the Songhua River Basin,northeastern China,from 2011 to 2015

The analysis of a large number of multidimensional surface water monitoring data for extracting potential information plays an important role in water quality management. In this study, growing hierarchical self-organizing map (GHSOM) was applied to a water quality assessment of the Songhua River Basin in China using 22 water quality parameters monitored monthly from 13 monitoring sites from 2011 to 2015 (14,782 observations). The spatial and temporal features and correlation between the water quality parameters were explored, and the major contaminants were identified. The results showed that the downstream of the Second Songhua River had the worst water quality of the Songhua River Basin. The upstream and midstream of Nenjiang River and the Second Songhua River had the best. The major contaminants of the Songhua River were chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), total phosphorus (TP), and fecal coliform (FC). In the Songhua River, the water pollution at downstream has been gradually eased in years. However, FC and biochemical oxygen demand (BOD₅) showed growth over time. The component planes showed that three sets of parameters had positive correlations with each other. GHSOM was found to have advantages over self-organizing maps and hierarchical clustering analysis as follows: (1) automatically generating the necessary neurons, (2) intuitively exhibiting the hierarchical inheritance relationship between the original data, and (3) depicting the boundaries of the classification much more clearly. Therefore, the application of GHSOM in water quality assessments, especially with large amounts of monitoring data, enables the extraction of more information and provides strong support for water quality management.     

Optimizing water quality monitoring networks using continuous longitudinal monitoring data: a case study of Wen-Rui Tang River, Wenzhou, China

Identification of representative sampling sites is a critical issue in establishing an effective water quality monitoring program. This is especially important at the urban-agriculture interface where water quality conditions can change rapidly over short distances. The objective of this research was to optimize the spatial allocation of discrete monitoring sites for synoptic water quality monitoring through analysis of continuous longitudinal monitoring data collected by attaching a water quality sonde and GPS to a boat. Sampling was conducted six times from March to October 2009 along a 6.5 km segment of the Wen-Rui Tang River in eastern China that represented an urban-agricultural interface. When travelling at a velocity of ～2.4 km h(-1), this resulted in water quality measurements at ～20 m interval. Ammonia nitrogen (NH(4)(+)-N), electrical conductivity (EC), dissolved oxygen (DO), and turbidity data were collected and analyzed using Cluster Analysis (CA) to identify optimal locations for establishment of long-term monitoring sites. The analysis identified two distinct water quality segments for NH(4)(+)-N and EC and three distinct segments for DO and turbidity. According to our research results, the current fixed-location sampling sites should be adjusted to more effectively capture the distinct differences in the spatial distribution of water quality conditions. In addition, this methodology identified river reaches that require more comprehensive study of the factors leading to the changes in water quality within the identified river segment. The study demonstrates that continuous longitudinal monitoring can be a highly effective method for optimizing monitoring site locations for water quality studies.     

Assessment of surface water quality using multivariate statistical techniques: a case study of Behrimaz Stream, Turkey

Multivariate statistical techniques, such as cluster analysis (CA), principal component analysis, and factor analysis, were applied for the evaluation of temporal/spatial variations and for the interpretation of a water quality data set of the Behrimaz Stream, obtained during 1 year of monitoring of 20 parameters at four different sites. Hierarchical CA grouped 12 months into two periods (the first and second periods) and classified four monitoring sites into two groups (group A and group B), i.e., relatively less polluted (LP) and medium polluted (MP) sites, based on similarities of water quality characteristics. Factor analysis/principal component analysis, applied to the data sets of the two different groups obtained from cluster analysis, resulted in five latent factors amounting to 88.32% and 88.93% of the total variance in water quality data sets of LP and MP areas, respectively. Varifactors obtained from factor analysis indicate that the parameters responsible for water quality variations are mainly related to discharge, temperature, and soluble minerals (natural) and nutrients (nonpoint sources: agricultural activities) in relatively less polluted areas; and organic pollution (point source: domestic wastewater) and nutrients (nonpoint sources: agricultural activities and surface runoff from villages) in medium polluted areas in the basin. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and interpretation of data sets and, in water quality assessment, identification of pollution sources/factors and understanding temporal/spatial variations in water quality for effective stream water quality management.     

Spatiotemporal trend analysis of recent river water quality conditions in Japan

In order to promote pollutant monitoring and preservation of water resources, we evaluate the spatiotemporal trends in recent water quality conditions in Japanese rivers. Trend analysis is conducted on the 92 major rivers in Japan using the available water quality data recorded from 1992 to 2005 and the characteristics of major pollutants in these rivers are analyzed. Spatial and temporal analysis of trends for six water quality indicators is conducted using the Mann Kendall test, a non-parametric statistical method. The indicators analyzed are biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP) and pH. The majority of sampling locations monitoring BOD, COD, TN and TP show trends toward decreasing concentrations over time. Many sampling locations show increasing DO concentrations. Our results show that water quality in Japanese rivers has improved dramatically over the past decade, although there are still problems in some places, most notably in the Hokkaido, Kanto, Kinki and Kyushu regions. The improvements seen in water quality appear to be the result of improved wastewater treatment and other water quality improvement efforts achieved through government initiative.     

Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters

The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.     

Using multivariate techniques as a strategy to guide optimization projects for the surface water quality network monitoring in the Velhas river basin,Brazil

Surface water quality monitoring networks are usually deployed and rarely re-evaluated with regard to their effectiveness. In this sense, this work sought to evaluate and to guide optimization projects for the water quality monitoring network of the Velhas river basin, using multivariate statistical methods. The cluster, principal components, and factorial analyses, associated with non-parametric tests and the analysis of violation to the standards set recommended by legislation, identified the most relevant water quality parameters and monitoring sites, and evaluated the sampling frequency. Thermotolerant coliforms, total arsenic, and total phosphorus were considered the most relevant parameters for characterization of water quality in the river basin. The monitoring sites BV156, BV141, BV142, BV150, BV137, and BV153 were considered priorities for maintenance of the network. The multivariate statistical analysis showed the importance of a monthly sampling frequency, specifically the parameters considered most important.     

Monitoring, assessment and modelling using water quality data in the Saale River Basin, Germany

The European Water Framework Directive (WFD) is the overall driver for this environmental study and currently requires the identification of patterns and sources of pollution (monitoring) to support objective ecological sound decision making and specific measures to enhance river water quality (modelling). The purpose of this paper is to demonstrate in a case study the interrelationship between (1) hydrologic and water quality monitoring data for river basin characterization and (2) modelling applications to assess resources management alternatives. The study deals with monitoring assessment and modelling of river water quality data of the main stem Saale River and its principal tributaries. For a period of 6 years the data, which was sampled by Environmental Agencies of the German states of Thuringia, Saxony and Saxony-Anhalt, was investigated to assess sources and indicators of pollution. In addition to the assessment a modelling exercise of the routing of different pollutants was carried out in the lower part of the test basin. The modelling is a tool to facilitate the evaluation of alternative measures to reduce contaminant loadings and improve ecological status of a water body as required by WFD. The transport of suspended solids, salts and heavy metals was modelled along a selected Saale reach under strong anthropogenic influence in terms of contaminants and river morphology between the city of Halle and the confluence with the Elbe River. The simulations were carried out with the model WASP5 which is a dynamic flood-routing and water quality model package developed by the US Environmental Protection Agency.     

化学需氧量和总有机碳在水质在线监测中的比较

化学需氧量（COD）和总有机碳（TOC）是定量表示水体受有机物污染的2个重要代表性指标。传统的COD在线监测方法在监测有机污染物方面存在一定的挑战,系统比较了COD和TOC在线监测方法在特殊水质中的应用。结果显示：TOC对难氧化有机物的氧化效率高达98%,高氯离子和无机还原性离子对TOC测量误差影响分别约为10%和7%。TOC可更直接、更准确地反映出水体受有机物污染的情况,最后对TOC指标在水质在线监测中的推广应用提出建议。     

湖州合溪新港污染物入湖通量估算与分析

根据2021年5月—2022年4月合溪新港河流水量、水质(TN和TP)的同步监测数据，利用通量模型核算了合溪新港污染物(TN和TP)通量。通过测算合溪新港TN、TP通量与断面降雨强度、水质的响应关系，分析了该区域的污染类型及特点，为后期水质污染调查及通量研究提供了新思路。结果表明：合溪新港流量与降雨量存在明显相关关系，在强降雨期(7—8月)水体流量最高，占监测周期总流量的57.77%;少雨期则流量最低，且会出现湖水倒灌现象(11—12月)。通过分析合溪新港TN、TP通量与流量、水质的相关关系，确定了该流域污染类型为点源污染及农业面源污染共存的混合型污染，且在高强度降雨时污染物负荷量较大。综上，可针对农业面源污染对该流域治理提出相关对策，建立农业面源污染防治体系，以有效降低TN和TP污染物的入湖通量，减少太湖TN和TP污染物负荷量。     

Evaluation of Water Quality in the Chillán River (Central Chile) Using Physicochemical Parameters and a Modified Water Quality Index

The Chillán River in Central Chile plays a fundamental role in local society, as a source of irrigation and drinking water, and as a sink for urban wastewater. In order to characterize the spatial and temporal variability of surface water quality in the watershed, a Water Quality Index (WQI) was calculated from nine physicochemical parameters, periodically measured at 18 sampling sites (January–November 2000). The results indicated a good water quality in the upper and middle parts of the watershed. Downstream of the City of Chillán, water quality conditions were critical during the dry season, mainly due to the effects of the urban wastewater discharge. On the basis of the results from a Principal Component Analysis (PCA), modifications were introduced into the original WQI to reduce the costs associated with its implementation. WQI_DIR2 and WQI_DIR, which are both based on a laboratory analysis (Chemical Oxygen Demand) and three (pH, temperature and conductivity), respectively, four field measurements (pH, temperature, conductivity and Dissolved Oxygen), adequately reproduce the most important spatial and temporal variations observed with the original index. They are proposed as useful tools for monitoring global water quality trends in this and other, similar agricultural watersheds in the Chilean Central Valley. Possibilities and limitations for the application of the used methodology to watersheds in other parts of the world are discussed.     

丹江口水库湖北库区水质分区及长期变化趋势

丹江口水库是南水北调中线工程水源地,准确地掌握丹江口水库水环境质量状况变化情况,对保障调水工程顺利进行有着极其重要的意义。基于水质理化指标将丹江口水库湖北库区水域划分为4个区,各分区的主要物理指标存在显著差异,化学指标较为均一;近10年水质历史监测数据显示,湖北库区除总氮指标外,其余监测指标水质类别均达到或优于Ⅱ类,总体水质保持优良;氨氮、总磷、总氮3项指标年均浓度从2007年起呈增加趋势,在2011年后均有所降低并趋于稳定。农业面源污染对丹江口水库水质影响较大。目前采取的各项环保措施对丹江口水库的水质产生了积极的影响,需继续加大各项治理措施的实施力度,完善水质监测系统,保障丹江口水库水质安全。     

CMT监测井在黑河流域地下水监测中的应用

以CMT监测井在黑河流域的应用为基础,通过对监测数据和采集的水样进行分析,了解了黑河流域地下水水位动态变化,掌握了黑河流域地下水水化学垂向分布规律,为合理利用黑河流域水资源提供了科学依据。     

Water quality in Lis river, Portugal

In the past 30?years, the Lis river basin has been subjected to constant ecological disasters mainly due to piggery untreated wastewater discharges. The aim of this study was to evaluate the effect of existing domestic, agricultural, and industrial activities on the water quality, and to propose a watershed plan to protect and manage surface water resources within the Lis river basin. For this purpose, 16 monitoring stations have been strategically selected along the Lis river stretch and its main tributaries to evaluate the water quality in six different sampling periods (2003–2006). All samples were characterized in terms of organic material, nutrients, chlorophyll, and pathogenic bacteria. Generally, the Lis river presents poor water quality, according to environmental quality standards for surface water, principally in terms of dissolved oxygen, biochemical oxygen demand, total nitrogen, and fecal coliform, which can be associated mainly with the contamination source from pig-breeding farms.     

Atmospheric influences on water quality: a simulation of nutrient loading for the Pearl River Basin, USA

Knowledge of water quality conditions is essential in assessing the health of riverine ecosystems. The goal of this study is to determine the degree to which water quality variables are related to precipitation and air temperature conditions for a segment of the Pearl River Basin near Bogalusa, LA, USA. The AQUATOX ecological fate simulation model is used to estimate daily total nitrogen, total phosphorus, and dissolved oxygen concentrations over a 2-year period. Daily modeled output for each variable was calibrated against reliably measured data to assess the accuracy. Observed data were plotted against simulated data for controlled and perturbed models for validation, and stepwise multiple regression analysis was used to quantify the relationships between the water quality and meteorological variables. Results suggest that daily dissolved oxygen is significantly negatively correlated to concurrent daily mean air temperature with a total explained variance of 0.679 (p?<?0.01), and monthly dissolved oxygen is significantly negatively correlated to monthly mean air temperature with a total explained variance of 0.567 (p?<?0.01). Total mean monthly phosphorus concentration is significantly positively related to the previous month's precipitation with a total explained variance of 0.302 (p?<?0.01). These relationships suggest that atmospheric conditions have a strong influence on water quality in the Pearl Basin. Therefore, environmental planners should expect that future climatic changes are likely to alter water quality.     

Temporal scale-induced uncertainty in load duration curves for instream-dissolved oxygen

Load duration curves were developed using the Hydrological Simulation Program FORTRAN (HSPF) for dissolved oxygen (DO) for the Amite River in Louisiana, USA. The concept of ‘dissolved oxygen reserve’, defined as the total quantity of DO, is introduced. The effect of temporal resolution on duration curves of DO reserve was examined using duration curves developed based on daily, weekly, biweekly, and monthly average data. Duration curves for DO exhibited high variability in the load estimated using daily data as compared to those based on biweekly and monthly data. A seasonal analysis revealed the trend in the DO reserve. The daily DO reserve for the Amite River at Port Vincent was 44,049.31 kg when daily summer data were used and 74,255.15 kg for daily annual data. A surplus of 10,691 kg of DO reserve was shown in the monthly data during critical summer months. The coefficient of variation (CV), used to define the temporal scale-induced uncertainty, was found to be linearly and inversely correlated with the logarithm of the time scale. Regression equations were developed to extrapolate near real-time flow and water quality data, greatly simplifying flow and water quality monitoring and reducing the cost involved in flow and water quality monitoring.     

Application of diatom biotic indices in the Guadalquivir River Basin, a Mediterranean basin. Which one is the most appropriated?

The diatom community was studied in 110 sites within the Guadalquivir River catchment area, South Spain, in order to test the applicability of diatom biotic indices developed in other European regions to this site and to provide a useful tool for monitoring water quality in the river basin. We identified 399 taxa and calculated five diatomic indices (Specific Polluosensitivity Index (IPS), Biological Diatom Index, Trophic Diatom Index, Index of the European Economic Community, and Diatom-based Eutrophication Pollution Index (EPI-D)). Since the indices analyzed were highly correlated, their results could be compared. The indices that gave the best results were the EPI-D followed by the IPS, the latter being the most widely used index in Iberian catchments. Nevertheless, the EPI-D presented certain advantages: (1) this index correlated the best with the water chemistry in the catchment area; (2) EPI-D is not sensitive to the presence of taxa belonging to the Achnanthidium minutissimum complex frequently present in the Guadalquivir basin. Nevertheless, EPI-D retains its effectiveness and thus constitutes an easier index for application from a taxonomical standpoint. We estimated the general water quality of the entire basin on the basis of EPI-D. According to these results, 55% of the sites had either high or good water quality. The species that better characterized each water quality category in the study area were: A. minutissimum (high and good), Amphora pediculus (moderate), Nitzschia frustulum (poor), and Nitzschia capitellata (bad).     

Testing taxonomic resolution levels for detecting environmental impacts using macrobenthic assemblages in tropical waters

Delta regions of the Cauvery River basin are one of the significant areas of rice production in India. In spite of large-scale utilization of the river basin for irrigation and drinking purposes, the lack of appropriate water management has seemingly deteriorated the water quality due to increasing anthropogenic activities. To assess the extent of deterioration, physicochemical characteristics of surface water were analyzed monthly in select regions of Cauvery Delta River basin, India, during July 2007 to December 2007. Total dissolved solids, chemical oxygen demand, and phosphate recorded maximum levels of 1,638, 96, and 0.43 mg/l, respectively, exceeding the permissible levels at certain sampling stations. Monsoonal rains in Cauvery River basin and the subsequent increase in river flow rate influences certain parameters like dissolved solids, phosphate, and dissolved oxygen. Agricultural runoff from watershed, sewage, and industrial effluents are suspected as probable factors of water pollution.     

Evaluation of surface water quality characteristics by using multivariate statistical techniques: A case study of the Euphrates river basin, Turkey

The surface water quality of the Euphrates river basin in Turkey are evaluated by using the multivariate statistical techniques known as factor analysis (FA) and multidimensional scaling (MDS) analysis. When FA was applied to the water quality data obtained from the 15 different surface water quality monitoring stations, two factors were identified, which were responsible from the 86.02% of the total variance of the water quality in the Euphrates river basin. The first factor called the urban land use factor explained 44.20% of the total variance and the second factor called the agricultural use factor explained 41.81% of the total variance. MDS technique showed that electrical conductivity (EC), percent sodium (Na%) and total salt are the most important variables causing difference in the water quality analysis.