Interpretation Of Water Quality Data Research Articles

Pengaruh Penggunaan Media Filtrasi Terhadap Kualitas Air Sumur Gali di Kota Sorong

Sorong City is a city in Southwest Papua Province, with an area of 1,105 km2. The need for clean water is not directly proportional to the mapping of clean water services provided by the government so far it has not reached 30% of the total population in the Sorong City Region. The aims of the study were to analyze the existing water quality in Sorong City, to analyze the effect of the filter media on the planned filtration device on the water quality of the research sample, and to analyze the cost of the planned filtration device. The method used is a qualitative method that is carried out is the monitoring and interpretation of water quality data including physical and chemical quality. Observations of water from dug wells in the City of Sorong have the quality or nature of water that smells, has a salty taste, and is slightly brown in color. Of the 3 samples analyzed according to the existing location, only 2 samples were quality standards, the effect of the filtration media on water quality from 3 samples. Filtration equipment with filtration media 1 has an average per parameter of sample 1 of 25.78%, sample 2 of 36.59%, and sample 3 of 21.86%. The filtration device with 2 filtration media has an average sample 1 of 34.24%, sample 2 of 49.51%, and sample 3 of 25.44%. The filtration device with 3 filtration media has an average sample 1 of 22.32%, sample 2 of 30.6%, and sample 3 of 20.87%. and the cost of making a filtration device with filtration media 1 is IDR 300,000.00, filtration media 2 is IDR 295,000.00, filtration media 3 is IDR 290,000.00. The recommended filtration device is one that uses 2 filtration media.

Community-Based Monitoring Detects Sources and Risks of Mining-Related Water Pollution in Zimbabwe

Although mining and mineral processing are vital for many economies in the Global South, they are associated with enormous challenges of managing potentially devastating environmental impacts. In contexts where environmental oversight agencies often lack financial and personal capacities to fulfill their role, community-based monitoring might be a valid alternative to monitor potential environmental impacts. In this study, we present the setup and the implementation of a citizen science project to monitor water quality parameters in a river downstream of a coal mining area in Hwange, Western Zimbabwe. In a joint effort over 1.5 years, community monitors and scientists took close to 800 water samples in the Deka River and effluent channels. The data allowed identifying sources of pollution and relating these to past and present mining activities. The primary source of acid mine drainage came from abandoned underground mine sites. Illegal mine water dumping from active mine sites accentuated the problem and resulted in fish kills and food risks for the local population. Concentrations of manganese, nickel and arsenic were exceeding national fresh water guidelines and international drinking water standards. Manganese concentrations exceeded guidelines by a factor of 70 resulting in a public health risk. In this study, we showed that community-based monitoring offers a promising approach to establish a high-quality dataset for assessing mining-related risks if the implementation of sampling protocols is followed tightly. The monitoring scheme significantly improves the collection and interpretation of water quality data in challenging contexts where governmental institutions and industrial players are not enforcing environmental standards.

Water Quality Modelling of River Mahanadi using Principal Component Analysis (PCA) and Multiple Linear Regression (MLR)

Surface water quality is one of the critical environmental concerns of the globe and water quality management is top priority worldwide. In India, River water quality has considerably deteriorated over the years and there is an urgent need for improving the surface water quality. The present study aims at use of multivariate statistical approaches for interpretation of water quality data of Mahanadi River in India. Monthly water quality data pertaining to 16 parameters collected from 12 sampling locations on the river by Central Water Commission (CWC) and Central Pollution Control Board (CPCB) is used for the study. Cluster analysis (CA), is used to group the sampling locations on the river into homogeneous clusters with similar behaviour. Principal component analysis (PCA) is quite effective in identifying the critical parameters for describing the water quality of the river in dry and monsoon seasons. PCA and Factor Analysis (FA) was effective in explaining 69 and 66% of the total cumulative variance in the water quality if dry and wet seasons respectively. Industrial and domestic wastewaters, soil erosion and weathering, soil leaching organic pollution and natural pollution were identified as critical sources contribution to pollution of river water. However, the quantitative contributions were variable based on the season. Results of multiple linear regression (MLR) are effective in explaining the factor loadings and source contributions for most water quality parameters. The study results indicate suitability of multivariate statistical approaches to design and plan sampling and sampling programs for controlling water quality management programs in river basins.

Impact of reduced anthropogenic emissions and century flood on the phosphorus stock, concentrations and loads in the Upper Danube

Patterns of changes in the concentration of total and soluble reactive phosphorus (TP, SRP) and suspended sediments at different flow levels from 1991 to 2013 in the Austrian Danube are statistically analyzed and related to point and diffuse emissions, as well as to extreme hydrological events. Annual loads are calculated with three methods and their development in time is examined taking into consideration total emissions and hydrological conditions. The reduction of point discharges achieved during the 1990s was well translated into decreasing TP and SRP baseflow concentrations during the same period, but it did not induce any change in the concentrations at higher flow levels nor in the annual transport of TP loads. A sharp and long-lasting decline in TP concentration, affecting all flow levels, took place after a major flood in 2002. It was still visible during another major flood in 2013, which recorded lower TP concentrations than its predecessor. Such decline could not be linked to changes in point or diffuse emissions. This suggests that, as a result of the flood, the river system experienced a significant depletion of its in-stream phosphorus stock and a reduced mobilization of TP rich sediments afterwards. This hypothesis is corroborated by the decoupling of peak phosphorus loads from peak maximum discharges after 2002. These results are highly relevant for the design of monitoring schemes and for the correct interpretation of water quality data in terms of assessing the performance of environmental management measures.

Study on Monthly Contamination Modification in Aquatic Metal Parameters at W2Sites’ Ground Water of Noghan and Ghaemabad Towns of Khonsar City, Iran, from October 2011 to September 2012

This paper represents a study of the aquatic metals’ parameters for the interpretation of water quality data. The data were obtained during a monitoring programme of the ground water quality of W2 sites at the Nogham and Ghaemabad towns of Khonsar city, Iran, from October 2011 to September 2012. A number of industries, comprising of textile and tanneries, have been established in this area. It is informed that effluents from these industries are directly discharged into the irrigation fields, ground water and surrounding land. As a result, the quality of fresh water is degraded in the study region. In all, seven parameters, including trace elements Zinc, Iron, Lead, Manganese, Mercury, Copper and Cadmium, have been monitored at two sampling stations of a hydrochemical survey conducted at a stretch of wells under study. The results represented that the point sources of contamination are responsible for affecting the water quality in this area.

Surface Water Quality Assessment of Lis River Using Multivariate Statistical Methods

This study presents the application of multivariate statistical tools for the evaluation of spatial variations and the interpretation of water quality data obtained in a monitoring program of Lis river basin surface water, Portugal. Twenty-seven physicochemical and microbiological parameters were determined in six water sampling campaigns at 16 monitoring sites during the period from September 2003 to November 2006. Correlation analysis, principal component analysis, and cluster analysis were performed to evaluate the main water pollution sources and to characterize the spatial distribution of water pollution profiles in river basin. The results achieved with the statistical methodologies led to distinguish natural and anthropogenic pollution sources. Additionally, monitoring sites with similar water pollution profile were identified, indicating that some monitoring locations can be changed to improve the spatial characterization of water quality in the river basin. CBO, CQO, P, and N were identified as significant variables affecting spatial variations, namely in the Lis river middle reach. Besides the identification of main pollution sources, the applied statistical tools were able to identify spatial patterns of water pollution in Lis river basin, which further helps in the reassessment of the number and location of monitoring sites.

Assessment of seasonal variations of chemical characteristics in surface water using multivariate statistical methods

Water pollution has become a growing threat to human society and natural ecosystems in the recent decades. Assessment of seasonal changes in water quality is important for evaluating temporal variations of river pollution. In this study, seasonal variations of chemical characteristics of surface water for the Chehelchay watershed in northeast of Iran was investigated. Various multivariate statistical techniques, including multivariate analysis of variance, discriminant analysis, principal component analysis and factor analysis were applied to analyze river water quality data set containing 12 parameters recorded during 13 years within 1995–2008. The results showed that river water quality has significant seasonal changes. Discriminant analysis identified most important parameters contributing to seasonal variations of river water quality. The analysis rendered a dramatic data reduction using only five parameters: electrical conductivity, chloride, bicarbonate, sulfate and hardness, which correctly assigned 70.2 % of the observations to their respective seasonal groups. Principal component analysis / factor analysis assisted to recognize the factors or origins responsible for seasonal water quality variations. It was determined that in each season more than 80 % of the total variance is explained by three latent factors standing for salinity, weathering-related processes and alkalinity, respectively. Generally, the analysis of water quality data revealed that the Chehelchay River water chemistry is strongly affected by rock water interaction, hydrologic processes and anthropogenic activities. This study demonstrates the usefulness of multivariate statistical approaches for analysis and interpretation of water quality data, identification of pollution sources and understanding of temporal variations in water quality for effective river water quality management.

Diel biogeochemical processes and their effect on the aqueous chemistry of streams: A review

This review summarizes biogeochemical processes that operate on diel, or 24-h, time scales in streams and the changes in aqueous chemistry that are associated with these processes. Some biogeochemical processes, such as those producing diel cycles of dissolved O 2 and pH, were the first to be studied, whereas processes producing diel concentration cycles of a broader spectrum of chemical species including dissolved gases, dissolved inorganic and organic carbon, trace elements, nutrients, stable isotopes, and suspended particles have received attention only more recently. Diel biogeochemical cycles are interrelated because the cyclical variations produced by one biogeochemical process commonly affect another. Thus, understanding biogeochemical cycling is essential not only for guiding collection and interpretation of water-quality data but also for geochemical and ecological studies of streams. Expanded knowledge of diel biogeochemical cycling will improve understanding of how natural aquatic environments function and thus lead to better predictions of how stream ecosystems might react to changing conditions of contaminant loading, eutrophication, climate change, drought, industrialization, development, and other factors.

Equivalence versus classical statistical tests in water quality assessments

To evaluate whether two unattended field organic carbon instruments could provide data comparable to laboratory-generated data, we needed a practical assessment. Null hypothesis statistical testing (NHST) is commonly utilized for such evaluations in environmental assessments, but researchers in other disciplines have identified weaknesses that may limit NHST's usefulness. For example, in NHST, large sample sizes change p-values and a statistically significant result can be obtained by merely increasing the sample size. In addition, p-values can indicate that observed results are statistically significantly different, but in reality the differences could be trivial in magnitude. Equivalence tests, on the other hand, allow the investigator to incorporate decision criteria that have practical relevance to the study. In this paper, we demonstrate the potential use of equivalence tests as an alternative to NHST. We first compare data between the two field instruments, and then compare the field instruments' data to laboratory-generated data using both NHST and equivalence tests. NHST indicated that the data between the two field instruments and the data between the field instruments and the laboratory were significantly different. Equivalence tests showed that the data were equivalent because they fell within a pre-determined equivalence interval based on our knowledge of laboratory precision. We conclude that equivalence tests provide more useful comparisons and interpretation of water quality data than NHST and should be more widely used in similar environmental assessments.

A GIS-Based Spatial-Multivariate Statistical Analysis of Water Quality Data in the Porsuk River, Turkey

Abstract The study offers a GIS-based multivariate statistical analysis strategy to assess river water quality. Multivariate statistical methods and Geographic Information System (GIS) technology have effectively been used for water quality management. Recognizing the fact that the use of standard statistical methods can be restrictive due to the complexity of water quality datasets, geospatial statistical methods have been recommended for the water quality assessment. The objective of the study was to explore the potential capabilities of GIS-based joint multivariate statistical analysis for water quality assessment of Porsuk River in Turkey. A well-known multivariate statistical technique, principal component analysis (PCA), is incorporated into a geographic database for interpretation of water quality data. To characterize spatial variability of water quality data, spatial PCA was performed on the basis of spatial autocorrelation. Application of the joint spatio-multivariate statistical analysis for interpretation of the water quality database offered a better understanding of the hydrochemistry in the study region.

Enterococci in the New Zealand environment: implications for water quality monitoring

Faecal enterococci ecology outside the host is of great relevance when using these organisms as indicators of water quality. As a complement to New Zealand epidemiological studies of bathing water quality and health risk, a study of the environmental occurrence of these organisms has been undertaken. Specific concerns over the use of enterococci derive from the unique situation in New Zealand which has few chlorinated sewage effluents, a high ratio of grazing animals to humans, and significant inputs of animal processing effluents into the environment. Human and animal faecal wastes are the main sources, with 106–107cfu/100ml found in human sewage. Analysis of domestic and feral animal faeces found enterococci in the range of 101–106cfu/g with considerable variation between species. The latter observations support the notion that a considerable proportion of the load in urban/rural catchments and waterways (typically 102–103 enterococci cfu/100ml) is derived from non-human sources. Previous studies of enterococci quiescence in marine/fresh waters indicate that they enter a non-growth phase, exposure to sunlight markedly reducing culturability on selective and non-selective media. Enterococci were also found to survive/multiply within specific non-faecal environments. Enterococci on degrading drift seaweed at recreational beaches exceeded seawater levels by 2–4 orders of magnitude, suggesting that expansion had occurred in this permissive environment with resultant potential to contaminate adjacent sand and water. These studies suggest that multiple sources, environmental persistence, and environmental expansion of enterococci within selected niches add considerable complexity to the interpretation of water quality data.

Enterococci in the New Zealand environment: Implications for water quality monitoring

Faecal enterococci ecology outside the host is of great relevance when using these organisms as indicators of water quality. As a complement to New Zealand epidemiological studies of bathing water quality and health risk, a study of the environmental occurrence of these organisms has been undertaken. Specific concerns over the use of enterococcj derive from the unique situation in New Zealand which has few chlorinated sewage effluents, a high ratio of grazing animals to humans, and significant inputs of animal processing effluents into the environment. Human and animal faecal wastes are the main sources, with 106–107cfu/100ml found in human sewage. Analysis of domestic and feral animal faeces found enterococci in the range of 101–106cfu/g with considerable variation between species. The latter observations support the notion that a considerable proportion of the load in urban/rural catchments and waterways (typically 102–103 enterococci cfu/100ml) is derived from non-human sources. Previous studies of enterococci quiescence in marine/fresh waters indicate that they enter a non-growth phase, exposure to sunlight markedly reducing culturability on selective and non-selective media. Enterococci were also found to survive/multiply within specific non-faecal environments. Enterococci on degrading drift seaweed at recreational beaches exceeded seawater levels by 2.4 orders of magnitude, suggesting that expansion had occurred in this permissive environment with resultant potential to contaminate adjacent sand and water. These studies suggest that multiple sources, environmental persistence, and environmental expansion of enterococci within selected niches add considerable complexity to the interpretation of water quality data.

Using Borehole Flow Logging To Optimize Hydraulic-Test Procedures In Heterogeneous Fractured Aquifers

Hydraulic properties of heterogeneous fractured aquifers are difficult to characterize, and such characterization usually requires equipment-intensive and time-consuming applications of hydraulic testing in situ. Conventional coring and geophysical logging techniques provide useful and reliable information on the distribution of bedding planes, fractures and solution openings along boreholes, but it is often unclear how these locally permeable features are organized into larger-scale zones of hydraulic conductivity. New boreholes flow-logging equipment provides techniques designed to identify hydraulically active fractures intersecting boreholes, and to indicate how these fractures might be connected to larger-scale flow paths in the surrounding aquifer. Potential complications in interpreting flowmeter logs include: 1) Ambient hydraulic conditions that mask the detection of hydraulically active fractures; 2) Inability to maintain quasi-steady drawdowns during aquifer tests, which causes temporal variations in flow intensity to be confused with inflows during pumping; and 3) Effects of uncontrolled background variations in hydraulic head, which also complicate the interpretation of inflows during aquifer tests. Application of these techniques is illustrated by the analysis of cross-borehole flowmeter data from an array of four bedrock boreholes in granitic schist at the Mirror Lake, New Hampshire, research site. Only two days of field operations were required to unambiguously identify the few fractures or fracture zones that contribute most inflow to boreholes in the CO borehole array during pumping. Such information was critical in the interpretation of water-quality data. This information also permitted the setting of the available string of two packers in each borehole so as to return the aquifer as close to pre-drilling conditions as possible with the available equipment.

Spatial Variation of River Water Quality: A Survey of the River Exe

River water quality is of considerable relevance to the geographer and a reconnaissance survey of the spatial variation of the specific conductance of stream water within the basin of the River Exe was undertaken by the authors. The spatial pattern defined by the more than 500 samples collected was mapped and an attempt has been made to interpret the results. Much of the variation was closely related to lithology, but land use was also found to exert a significant influence on levels of conductivity. The data collected have also been used to obtain estimates of the magnitude and spatial pattern of annual solute loads and of chemical denudation rates. DURING the past 25 years, increasing attention has been focused upon spatial and temporal variations in the magnitude of streamflow or river discharge in Great Britain. Regional water resource studies have assessed the volumes of run-off available in particular areas, suggesting ways in which water can be stored and regulated.1 Furthermore, the problems of floods and droughts have stimulated the development of techniques for evaluating and predicting floods and low flows.2 Data on the flow of rivers in the British Isles are now available in the Surface Water Yearbook3 and additional information is being collected from several research basins.4 Geographers have been aware of the opportunities and relevance of this field of study and they have themselves made contributions.5 Much less information is available on the quality, as distinct from the quantity of streamflow. Detailed work in this sphere has previously been the province of the chemist and public health engineer and has been primarily concerned with the potability of sources of water supply and the nature and extent of serious pollution and the various possibilities available for the control or alleviation of this problem.6 With the increasing concern over the optimum use and management of water supplies in this country, more interest is being directed towards collection and interpretation of water quality data. River temperatures have already attracted the investigations of several workers,7 and studies of nitrate levels8 and solute transport by local streams have also been made.9 The quality of river water is not without relevance to the geographer, as Douglaso1 has recently emphasized. Water quality constitutes a valuable environmental indicator, reflecting the interaction of the quality of the incident precipitation with the character of the catchment area, the processes operating in the drainage basin, and the influence of man. It is in this context that Perel'manll has promoted the concept of geochemical environments or landscapes whereby geochemical indicators can be used for landscape classification or regionalization. In turn, water quality is an important control on human activity and resource utilization.12 Minimum quality standards exist for the various uses of water13 and severe negative feedbacks can occur where man-induced deterioration in water quality inhibits continued or more intensive use of water I55 This content downloaded from 207.46.13.111 on Sun, 07 Aug 2016 05:15:25 UTC All use subject to http://about.jstor.org/terms D.E.WALLING AND B.W.WEBB resources. Because of the significance to the operation of geomorphological processes, physical geographers have already made considerable progress towards understanding the solution chemistry and water quality of limestone areas.14 However, there is considerable scope for studies in non-limestone areas. For example, spectral analysis has been shown to be a powerful tool when studying temporal variations in solute concentrations,15 and the evaluation and interpretation of spatial variations in river water quality would seem to be another worthwhile theme for investigation. There are many indices of river water quality including, colour, odour, temperature, turbidity, solute content and other chemical and biological parameters, and these will exhibit spatial and temporal variations to a greater or lesser extent. Solute content and the concentration of individual ions provide a sensitive environmental indicator. For example, Miller16 has shown how solute concentrations can vary according to rock type; classic studies in the Hubbard Brook experimental catchment in New Hampshire, U.S.A.17 have stressed the interdependence of concentrations of individual ions and the nutrient cycle; and Skakalskiyl8 has demonstrated how solute concentrations can be related to the magnitude and origins of different run-off components. In addition, many reports exist of the influence of man on these parameters.19 Temporal variations in solute concentrations have been well documented by workers such as Hendrickson and Krieger20 and Hall,21 and spatial contrasts have been discussed on a world scale by Gibbs,22 on a continental scale by Rainwater,23 at the regional level by Douglas,24 and within a drainage basin by Anderson and George.25

Graphical interpretation of water quality data

Management of our nation's water resources through planning and control of water pollution hinges on the availability and interpretation of water quality data on which to base management decisions. This paper is aimed at exploring graphical methods which allow rapid and informative analysis of water quality data. The graphical methods presented in this paper fall into two main categories. The first category relates to graphical procedures which are developed as part of a statistical test, such as discriminant analysis. The second category involves approximation of multivariate water quality data into two dimensions. The methods for accomplishing the latter are canonical decomposition and high-dimensional plotting. Each of these methods is developed and used on an example set of data to demonstrate their utility. These methods seek to not only present a graphical representation of the data, but also to explain variations and interrelationships within the data itself.

A Quality Assurance Program for Water Quality Monitoring Studies

Abstract Requirements for the collection and interpretation of water quality data have increased in recent years. The development of a quality assurance program is a necessity to insure the validity of the data. Such a program is described for application in environmental impact assessments.