Post-reclamation water quality trend in a Mid-Appalachian watershed of abandoned mine lands

Abandoned mine land (AML) is one of the legacies of historic mining activities, causing a wide range of environmental problems worldwide. A stream monitoring study was conducted for a period of 7 years to evaluate the water quality trend in a Mid-Appalachian watershed, which was heavily impacted by past coal mining and subsequently reclaimed by reforestation and revegetation. GIS tools and multivariate statistical analyses were applied to characterize land cover, to assess temporal trends of the stream conditions, and to examine the linkages between water quality and land cover. In the entire watershed, 15.8% of the land was designated as AML reclaimed by reforestation (4.9%) and revegetation (10.8%). Statistic analysis revealed sub-watersheds with similar land cover (i.e. percentage of reclaimed AML) had similar water quality and all tested water quality variables were significantly related to land cover. Based on the assessment of water quality, acid mine drainage was still the dominant factor leading to the overall poor water quality (low pH, high sulfate and metals) in the watershed after reclamation was completed more than 20 years ago. Nevertheless, statistically significant improvement trends were observed for the mine drainage-related water quality variables (except pH) in the reclaimed AML watershed. The lack of pH improvement in the watershed might be related to metal precipitation and poor buffering capacity of the impacted streams. Furthermore, water quality improvement was more evident in the sub-watersheds which were heavily impacted by past mining activities and reclaimed by reforestation, indicating good reclamation practice had positive impact on water quality over time.     

The Use of an Objective Index for the Assessment of the Contamination of Surface Water and Groundwater by Acid Mine Drainage

Temporal and spatial comparisons of acid mine-drainage contaminated waters are difficult because of the complex physico-chemical nature of the pollutant, and an objective index has been developed and evaluated for the assessment of such waters. The acid mine-drainage index is calculated using a modified arithmetic weighted index utilizing seven parameters which are most indicative of acid mine-drainage contamination, i.e. pH value, sulphate, iron, zinc, aluminium, copper and cadmium. Weighting is used to express the relative indicator value of each parameter. pH and sulphate are considered to be of greatest indicator value as they are unaffected by sorption processes, while sulphate is also unaffected by natural neutralization processes. The acid mine-drainage index, as proposed, is designed to detect and quantify contamination from acid mine drainage, and to help categorize samples, quantify impact and to monitor the recovery of receiving waters.     

The impact of sunlight on inactivation of indicator microorganisms both in river water and benthic biofilms

A detailed knowledge on decay or inactivation kinetics of faecal indicator microorganism in rivers is essential for control of bathing water quality. Both reliable inactivation rate coefficients for such kinetics and the knowledge on pathogen accumulation in benthic biofilms are needed for the assessment of river self purification capability and for being able to make decisions for an optimized water management. Therefore, the inactivation kinetics for main indicator microorganisms like faecal coliforms and intestinal Enterococci in water and on stones of the river Isar (Germany) were measured at artificial sunlight radiation. A flume was built, containing Isar water and sediment. By adding a pulse of pre-treated sewage water, the subsequently change of indicator bacteria levels in the bulk and biofilm phase is measured. Bacterial inactivation was mainly dependent on sunlight intensity. Mean inactivation rate coefficients in the experimental set up with river water obtained for a radiation intensity comparable to average midday sunlight in June in 50 degrees north latitude (I((290-390nm))=40.0W/m(2)) were found to be 21.4d(-1) for faecal coliforms and 20.0d(-1) for intestinal Enterococci. For a radiation intensity conform with the annual mean radiation in Germany (I((290-390nm))=8.0W/m(2)) inactivation rate coefficients were 12.7d(-1) for faecal coliforms and 9.3d(-1) for intestinal Enterococci. A measurement without direct artificial sunlight (I((290-390nm))=0.08W/m(2)) yields inactivation rate coefficients of 3.4d(-1) for faecal coliforms and 1.7d(-1) for intestinal Enterococci, which were similar to those found in wastewater treatment ponds. Due to re-growth and better environmental conditions the concentrations of faecal coliforms and intestinal Enterococci within the biofilm were 10(2) to 10(4) fold higher compared to the bulk water depending on the exposure time.     

Application of chemometrics in river water classification

The main aim of this work is focused on water quality classification of the Brda river (Poland) and evaluation of pollution data obtained by the monitoring measurement during the period 1994-2002. The study presents the application of selected chemometric techniques to the pollution monitoring dataset, namely, cluster analysis, principal component analysis, discriminant analysis and factor analysis. The obtained results allowed to determine natural clusters and groups of monitoring locations with similar pollution character and identify important discriminant variables. Chemometric analysis confirmed the classification of water purity of the Brda river made by the Inspection of Environmental Protection but the results showed more differentiation between monitored locations. This enables better evaluation of the water quality in a monitored region. On the basis of the chemometric approach, it was also found that some locations were under the high influence of municipal contamination, and some others under the influence of agriculture (discharges from fields) within the observed time period.     

潮河流域水质分析研究

指出潮河是密云水库支柱水源，潮河的水质关系到北京人民的身体健康，采用“水质综合评价法”对潮河水质进行了分析，结果表明潮河上游水质状况良好，适合作为城市水源地水源。     

Pesticide contamination and phytotoxicity of sediment interstitial water to tropical benthic microalgae

Many organic compounds including some herbicides concentrate in sediment, thus it may be expected that interstitial waters contain higher concentrations of these contaminants than the water column. To estimate benthic microalgal exposure to pesticides, sediment and interstitial water sampled in the dry season from four major rivers in north Queensland, Australia, were analysed for these contaminants. Interstitial water extracts from the sediments were tested for acute phytotoxicity to benthic microalgae using PAM fluorometry and the results were compared with chemical analyses of the same water samples. A range of pesticides were detected in both sediment and interstitial waters from all sites, notably the herbicide diuron at concentrations ranging from 0.3 to 11 μg kg⁻¹ dry weight sediment, and up to 68 ng L⁻¹ in interstitial waters. Herbicide concentrations estimated from partition coefficients and the sediment concentrations typically overestimated analytically determined concentrations present in interstitial water by an order of magnitude. The analytically determined herbicide concentrations in the interstitial water explained most of the phytotoxicity measured with the bioassay; however, photoinhibition was slightly higher than expected based on analytical results, indicating the presence of unidentified phytotoxins. These results demonstrate the presence of pesticides in interstitial waters in the Tropical dry season, sometimes at concentrations that may affect sensitive benthic organisms, and supports the use of the I-PAM bioassay as a valuable tool in exposure- and environmental risk- and impact-assessments.     

Environmental impact of mining activities in the Lousal area (Portugal): chemical and diatom characterization of metal-contaminated stream sediments and surface water of Corona stream

Lousal mine is a typical “abandoned mine” with all sorts of problems as consequence of the cessation of the mining activity and lack of infrastructure maintenance. The mine is closed at present, but the heavy metal enriched tailings remain at the surface in oxidizing conditions. Surface water and stream sediments revealed much higher concentrations than the local geochemical background values, which the “Contaminated Sediment Standing Team” classifies as very toxic. High concentrations of Cu, Pb, Zn, As, Cd and Hg occurred within the stream sediments downstream of the tailings sites (up to: 817 mg kg⁻¹ As, 6.7 mg kg⁻¹ Cd, 1568 mg kg⁻¹ Cu, 1059 mg kg⁻¹ Pb, 82.4 mg kg⁻¹ Sb, 4373 mg kg⁻¹ Zn). The AMD waters showed values of pH ranging from 1.9 to 2.9 and concentrations of 9249 to 20,700 mg L⁻¹ SO₄⁻², 959 to 4830 mg L⁻¹ Fe and 136 to 624 mg L⁻¹ Al. Meanwhile, the acid effluents and mixed stream waters also carried high contents of SO₄^2−, Fe, Al, Cu, Pb, Zn, Cd, and As, generally exceeding the Fresh Water Aquatic Life Acute Criteria. Negative impacts in the diatom communities growing at different sites along a strong metal pollution gradient were shown through Canonical Correspondence Analysis: in the sites influenced by Acid Mine Drainage (AMD), the dominant taxon was Achnanthidium minutissimum. However, Pinnularia acoricola was the dominant species when the environmental conditions were extremely adverse: very low pH and high metal concentrations (sites 2 and 3). Teratological forms of Achnanthidium minutissimum (Kützing) Czarnecki, Brachysira vitrea (Grunow) Ross in Hartley, Fragilaria rumpens (Kützing) G. W. F. Carlson and Nitzschia hantzschiana Rabenhorst were found. A morphometric study of B. vitrea showed that a decrease in size was evident at the most contaminated sites. These results are evidence of metal and acidic pollution.     

Comparing microbial water quality in an intermittent and continuous piped water supply

Supplying piped water intermittently is a common practice throughout the world that increases the risk of microbial contamination through multiple mechanisms. Converting an intermittent supply to a continuous supply has the potential to improve the quality of water delivered to consumers. To understand the effects of this upgrade on water quality, we tested samples from reservoirs, consumer taps, and drinking water provided by households (e.g. from storage containers) from an intermittent and continuous supply in Hubli–Dharwad, India, over one year. Water samples were tested for total coliform, Escherichia coli, turbidity, free chlorine, and combined chlorine. While water quality was similar at service reservoirs supplying the continuous and intermittent sections of the network, indicator bacteria were detected more frequently and at higher concentrations in samples from taps supplied intermittently compared to those supplied continuously (p < 0.01). Detection of E. coli was rare in continuous supply, with 0.7% of tap samples positive compared to 31.7% of intermittent water supply tap samples positive for E. coli. In samples from both continuously and intermittently supplied taps, higher concentrations of total coliform were measured after rainfall events. While source water quality declined slightly during the rainy season, only tap water from intermittent supply had significantly more indicator bacteria throughout the rainy season compared to the dry season. Drinking water samples provided by households in both continuous and intermittent supplies had higher concentrations of indicator bacteria than samples collected directly from taps. Most households with continuous supply continued to store water for drinking, resulting in re-contamination, which may reduce the benefits to water quality of converting to continuous supply.     

The impact of new developments on river water quality from an integrated system modelling perspective

New housing areas are a ubiquitous feature of modern life in the developing and developed world alike built in response to rising social, demographic and economic pressures. Inevitably, these new developments will have an impact on the environment around them. Empirical evidence confirms the close relationship between urbanisation and ambient water quality. However, what is lacking so far is a detailed and more generalised analysis of environmental impact at a relatively small scale. The aim of this paper is to quantify the impact of new developments on river water quality within an integrated system modelling perspective. To conduct the impact analyses, an existing integrated urban wastewater model was used to predict water flow and quality in the sewer system, treatment plant and receiving water body. The impact on combined sewer overflow (CSO) discharges, treatment plant effluent, and within the river at various reaches is analysed by ‘locating’ a new development on a semi-hypothetical urban catchment. River water quality is used as feedback to constrain the scale of the new development within different thresholds in compliance with water quality standards. Further, the regional sensitivity analysis (RSA) method is applied to reveal the parameters with the greatest impact on water quality. These analyses will help to inform town planners and water specialists who advise them, how to minimise the impact of such developments given the specific context.     

Treated water quality assurance and description of distribution networks by multivariate chemometrics

Throughout the year 2007, 89 treated water samples from three water treatment plants (WTPs) of the Athens Water Supply and Sewerage Company (EYDAP S.A.) and 180 samples from network tanks (NWTs) were analyzed for electrical conductivity (EC), alkalinity (TA), pH, aluminium (Al), total hardness (TH), chloride (Cl⁻), residual chlorine (free Cl), calcium (Ca²⁺) and magnesium (Mg²⁺). The results regarding the WTPs were subjected to a principal component analysis (PCA) with 75% of the total variance being explained. A stepwise linear discriminant analysis (LDA) model constructed from the 89 treated water samples was used to predict class membership of the samples from the NWTs with a view to estimating the propagation of a possible water quality deterioration originating from the WTPs. The model utilized Cl⁻, Al and EC and yielded a 96% correct classification of the training dataset, whereas the cross-validation yielded a 94% correct classification. Network tank samples were 95% correctly classified with regard to their theoretically expected origin. The stepwise discriminant analysis based on separate covariance matrices of the canonical discriminant functions yielded a 98% correct classification of both the training dataset and the network tank samples. The classification and regression tree (C&RT) algorithm showed that the main parameters used in the discrimination of the WTP samples were EC and Al. The post-hoc classification of the training dataset was 99%, whereas 88% of NWT samples were correctly classified.     

Influence of temperature and river discharge on water quality of the western scheldt estuary

Dissolved oxygen concentrations and information on the nitrification process collected respectively during a 14- and a 5-year period in the self-purifying part of the Western Scheldt estuary have been studied. In the polluted part of the stream, ammonium concentrations over the period 1967–1977 have been considered as well.This paper demonstrates the high variability of these 3 parameters (oxygen, start of the nitrification process, ammonium) owing to the hydrological conditions: temperature and river discharge.Neither the levels of ammonium in the polluted upper part of the stream, nor the concentrations of nitrate and dissolved oxygen in the recuperation part of the Scheldt estuary have changed significantly during the periods studied (respectively 5, 10 and 14 years). A relation between these parameters and time could be hidden by hydrological factors.Water quality of a stream can be assessed by interpreting oxygen, nitrate, and ammonium concentrations, only if all environmental and hydrodynamical parameters are known simultaneously.     

Influence of water quality on the presence of off-flavour compounds (geosmin and 2-methylisoborneol)

Geosmin and 2-methylisoborneol are off-flavour compounds related to poor organoleptics and a decrease in consumer satisfaction with drinking water. The relationship between these off-flavour compounds and 39 parameters of water quality (chemical, physical and biological) for three different surface waters from lotic systems that supply potable water to Quebec City and Lévis (Canada) was studied using principal component analysis. The objective of this study was to show that a multidimensional approach with principal component analysis using the component matrix serves to differentiate the processes involved in the appearance of the olfactory compounds from those not involved or little involved and to extract the most representative data of these processes. Our study shows that the presence of geosmin can be explained, in the case of the water studied, by a process associated primarily with the eutrophication of water and, to a lesser degree, by an allochthonous origin. However, the presence of 2-methylisoborneol may be linked to two processes with different origins, but of equal importance: a winter origin – most likely allochthonous – involving anthropic contributions and an autochthonous bacterial origin.     

Evaluation of river water quality monitoring stations by principal component analysis

The development of a surface water monitoring network is a critical element in the assessment, restoration, and protection of stream water quality. This study applied principal component analysis (PCA) and principal factor analysis (PFA) techniques to evaluate the effectiveness of the surface water quality-monitoring network in a river where the evaluated variables are monitoring stations. The objective was to identify monitoring stations that are important in assessing annual variations of river water quality. Twenty-two stations used for monitoring physical, chemical, and biological parameters, located at the main stem of the lower St. Johns River in Florida, USA, were selected for the purpose of this study. Results show that 3 monitoring stations were identified as less important in explaining the annual variance of the data set, and therefore could be the non-principal stations. In addition, the PFA technique was also employed to identify important water quality parameters. Results reveal that total organic carbon, dissolved organic carbon, total nitrogen, dissolved nitrate and nitrite, orthophosphate, alkalinity, salinity, Mg, and Ca were the parameters that are most important in assessing variations of water quality in the river. This study suggests that PCA and PFA techniques are useful tools for identification of important surface water quality monitoring stations and parameters.     

煤质对煤泥水性质的影响及处理技术研究

通过一定的技术处理手段使得煤炭资源的质量和煤泥水的性质得到稳定,对煤业环保质量的提升以及促进国内相关企业的高效发展,提升经济效益等方面都具有非常重要的作用。本文中就将对煤质对煤泥水性质的影响及处理技术进行相关的研究和分析,对长焰煤以及无烟煤的煤泥水作为主要的研究对象,通过试验对比混凝剂与絮凝剂的选择及其剂量对其的影响,从而发现提升煤炭资源质量和煤泥水的稳定性的因素。     

Assessment of the surface water quality in Northern Greece

The application of different multivariate statistical approaches for the interpretation of a large and complex data matrix obtained during a monitoring program of surface waters in Northern Greece is presented in this study. The dataset consists of analytical results from a 3-yr survey conducted in the major river systems (Aliakmon, Axios, Gallikos, Loudias and Strymon) as well as streams, tributaries and ditches. Twenty-seven parameters have been monitored on 25 key sampling sites on monthly basis (total of 22,350 observations). The dataset was treated using cluster analysis (CA), principal component analysis and multiple regression analysis on principal components. CA showed four different groups of similarity between the sampling sites reflecting the different physicochemical characteristics and pollution levels of the studied water systems. Six latent factors were identified as responsible for the data structure explaining 90% of the total variance of the dataset and are conditionally named organic, nutrient, physicochemical, weathering, soil-leaching and toxic-anthropogenic factors. A multivariate receptor model was also applied for source apportionment estimating the contribution of identified sources to the concentration of the physicochemical parameters. This study presents the necessity and usefulness of multivariate statistical assessment of large and complex databases in order to get better information about the quality of surface water, the design of sampling and analytical protocols and the effective pollution control/management of the surface waters.     

Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis

22 Physico-chemical variables have been analyzed in water samples collected every three months for two and a half years from three sampling stations located along a section of 25 km of a river affected by man-made and seasonal influences. Exploratory analysis of experimental data have been carried out by box plots, ANOVA, display methods (principal component analysis) and unsupervised pattern recognition (cluster analysis) in an attempt to discriminate sources of variation of water quality. PCA has allowed the identification of a reduced number of “latent” factors with a hydrochemical meaning: mineral contents, man-made pollution and water temperature. Spatial (pollution from anthropogenic origin) and temporal (seasonal and climatic) sources of variation affecting quality and hydrochemistry of river water have been differentiated and assigned to polluting sources. An ANOVA of the rotated principal components has demonstrated that (i) mineral contents are seasonal and climate dependent, thus pointing to a natural origin for this polluting form and (ii) pollution by organic matter and nutrients originates from anthropogenic sources, mainly as municipal wastewater. The application of PCA and cluster analysis has achieved a meaningful classification of river water samples based on seasonal and spatial criteria.     

Applying global sensitivity analysis to the modelling of flow and water quality in sewers

While several approaches for global sensitivity analysis (GSA) have been proposed in literature, only few applications exist in urban drainage modelling. This contribution discusses two GSA methods applied to a sewer flow and sewer water quality model: Standardised Regression Coefficients (SRCs) using Monte-Carlo simulation as well as the Morris Screening method. For selected model variables we evaluate how the sensitivities are influenced by the choice of the rainfall event. The aims are to i) compare both methods concerning the similarity of results and their applicability, ii) discuss the implications for factor fixing (identifying non-influential parameters) and factor prioritisation (identifying important parameters) and iii) rank the important parameters for the investigated model. It was shown that both methods lead to similar results for the hydraulic model. Parameter interactions and non-linearity were identified for the water quality model and the parameter ranking differs between the methods. For the investigated model the results allow a sound choice of output variables and rainfall events in view of detailed uncertainty analysis or model calibration. We advocate the simultaneous use of both methods for a first model assessment as they allow answering both factor fixing and factor prioritisation at low computational cost.     

Non-linear effects on solute transfer between flowing water and a sediment bed

A previously developed model of periodic pore water flow in space and time, and associated solute transport in a stream bed of fine sand is extended to coarse sand and fine gravel. The pore water flow immediately below the sediment/water interface becomes intermittently a non-Darcy flow. The periodic pressure and velocity fluctuations considered are induced by near-bed coherent turbulent motions in the stream flow; they penetrate from the sediment/water interface into the sediment pore system and are described by a wave number (χ) and a period (T) that are given as functions of the shear velocity (U_∗) between the flowing water and the sediment bed. The stream bed has a flat surface without bed forms. The flow field in the sediment pore system is described by the continuity equation and a resistance law that includes both viscous (Darcy) and non-linear (inertial) effects. Simulation results show that non-linear (inertial) effects near the sediment/water interface increase flow resistance and reduce mean flow velocities. Compared to pure Darcy flow, non-linear (inertial) effects reduce solute exchange rates between overlying water and the sediment bed but only by a moderate amount (less than 50%). Turbulent coherent flow structures in the stream flow enhance solute transfer in the pore system of a stream bed compared to pure molecular diffusion, but by much less than standing surface waves or bed forms.     

Estimating the effect of water quality on surface water supplies

River quality models derived by regression analysis are often quick and cheap to produce. They can be used as a basis for forecasting river quality and to calculate the effects of water quality constraints on the operation of water supplies drawn from rivers and impoundments. Results for nitrate show that to operate intakes according to river quality is a poor method of controlling quality in impoundments.     

Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)--a case study

This case study reports different multivariate statistical techniques applied for evaluation of temporal/spatial variations and interpretation of a large complex water-quality data set obtained during monitoring of Gomti River in Northern part of India. Water quality of the Gomti River, a major tributary of the Ganga River was monitored at eight different sites selected in relatively low, moderate and high pollution regions, regularly over a period of 5 years (1994-1998) for 24 parameters. The complex data matrix (17,790 observations) was treated with different multivariate techniques such as cluster analysis, factor analysis/principal component analysis (FA/PCA) and discriminant analysis (DA). Cluster analysis (CA) showed good results rendering three different groups of similarity between the sampling sites reflecting the different water-quality parameters of the river system. FA/PCA identified six factors, which are responsible for the data structure explaining 71% of the total variance of the data set and allowed to group the selected parameters according to common features as well as to evaluate the incidence of each group on the overall variation in water quality. However, significant data reduction was not achieved, as it needed 14 parameters to explain 71% of both the temporal and spatial changes in water quality. Discriminant analysis showed the best results for data reduction and pattern recognition during both temporal and spatial analysis. Discriminant analysis showed five parameters (pH, temperature, conductivity, total alkalinity and magnesium) affording more than 88% right assignations in temporal analysis, while nine parameters (pH, temperature, alkalinity, Ca-hardness, DO, BOD, chloride, sulfate and TKN) to afford 91% right assignations in spatial analysis of three different regions in the basin. Thus, DA allowed reduction in dimensionality of the large data set, delineating a few indicator parameters responsible for large variations in water quality. This study presents necessity and usefulness of multivariate statistical techniques for evaluation and interpretation of large complex data sets with a view to get better information about the water quality and design of monitoring network for effective management of water resources.