scholarly journals A Multivariate and Spatiotemporal Analysis of Water Quality in Code River, Indonesia

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mochamad A. Pratama ◽  
Yan D. Immanuel ◽  
Dwinanti R. Marthanty
Keyword(s):  
Water Quality ◽  
Land Cover ◽  
Agricultural Land ◽  
Water Quality Management ◽  
Temporal Trends ◽  
Oxygen Demand ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Water Quality Data

The efficacy of a water quality management strategy highly depends on the analysis of water quality data, which must be intensively analyzed from both spatial and temporal perspectives. This study aims to analyze spatial and temporal trends in water quality in Code River in Indonesia and correlate these with land use and land cover changes over a particular period. Water quality data consisting of 15 parameters and Landsat image data taken from 2011 to 2017 were collected and analyzed. We found that the concentrations of total dissolved solid, nitrite, nitrate, and zinc had increasing trends from upstream to downstream over time, whereas concentrations of parameter biological oxygen demand, cuprum, and fecal coliform consistently undermined water quality standards. This study also found that the proportion of natural vegetation land cover had a positive correlation with the quality of Code River’s water, whereas agricultural land and built-up areas were the most sensitive to water pollution in the river. Moreover, the principal component analysis of water quality data suggested that organic matter, metals, and domestic wastewater were the most important factors for explaining the total variability of water quality in Code River. This study demonstrates the application of a GIS-based multivariate analysis to the interpretation of water quality monitoring data, which could aid watershed stakeholders in developing data-driven intervention strategies for improving the water quality in rivers and streams.

scholarly journals Monitoring Lotic Ecosystem by the Application of Water Quality Index (CCMEWQI)

2020 ◽  
Vol 17 (1) ◽  
pp. 0023
Author(s):  
Salman Et al.
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Water Quality Management ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Total Hardness ◽  
Water Quality Data ◽  
Quality Of Water ◽  
Lotic Ecosystem

Water Quality Index (WQI) as a tool to assess the water quality status provides advice related to the use of water quality monitoring data and it is a way for combining the complex water quality data into a single value or single statement.The present study was conducted on Al- Hilla river in the middle of Iraq from August 2012 to July 2013 at five selected stations in the river, from Al- Musaib city to Al- Hashimya at the south of Hilla to determine its suitability for aquatic environment (GWQI), drinking water (PWSI) and irrigation (IWQI).This index offers a useful representation of the overall quality of water for public or any intended use as well as indicating pollution, water quality management, and decision making. According to the obtained results, it can be concluded that the EC, TSS, Total hardness, Ca, Mg, DO, BOD5, and NO3 moved away from the desired standards when the temperature rises. The variable of value of this index may be due to increasing the ration of organic matters and converting the carbonate to bicarbonate. The results recorded high value of calcium and magnesium more than the standard value of WHO and IQS (50 mg/l and high value of total hardness more than 500 mg/l). Irrigation water quality index (IWQI) in the study sites were ranged between 66-83 ranged between fair and good.                                                  

scholarly journals Investigation of the Soan River Water Quality Using Multivariate Statistical Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Zakaullah ◽  
Naeem Ejaz
Keyword(s):  
Water Quality ◽  
River Water ◽  
Water Quality Management ◽  
Oxygen Demand ◽  
River Water Quality ◽  
Quality Data ◽  
Spatiotemporal Pattern ◽  
Multivariate Statistical ◽  
Water Quality Data

Evaluating the quality of river water is a critical process due to pollution and variations of natural or anthropogenic origin. For the Soan River (Pakistan), seven sampling sites were selected in the urban area of Rawalpindi/Islamabad, and 18 major chemical parameters were examined over two seasons, i.e., premonsoon and postmonsoon 2019. Multivariate statistical approaches such as the Spearman correlation coefficient, cluster analysis (CA), and principal component analysis (PCA) were used to evaluate the water quality of the Soan River based on temporal and spatial patterns. Analytical results obtained by PCA show that 92.46% of the total variation in the premonsoon season and 93.11% in the postmonsoon season were observed by only two loading factors in both seasons. The PCA and CA made it possible to extract and recognize the origins of the factors responsible for water quality variations during the year 2019. The sampling stations were grouped into specific clusters on the basis of the spatiotemporal pattern of water quality data. The parameters dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), turbidity, and total suspended solids (TSS) are among the prominent contributing variations in water quality, indicating that the water quality of the Soan River deteriorates gradually as it passes through the urban areas, receiving domestic and industrial wastewater from the outfalls. This study indicates that the adopted methodology can be utilized effectively for effective river water quality management.

Long-term variations of water quality in a reservoir in China

2012 ◽  
Vol 65 (8) ◽  
pp. 1454-1460 ◽  
Author(s):  
Y. Y. Chen ◽  
C. Zhang ◽  
X. P. Gao ◽  
L. Y. Wang
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Temporal Trends ◽  
Oxygen Demand ◽  
Temporal Variations ◽  
Quality Parameters ◽  
Quality Data ◽  
Water Quality Data ◽  
Yuqiao Reservoir

To study the spatial and temporal trends of water quality in the Yuqiao Reservoir (Ji County, Tianjin) in China, water quality data for ten physical and chemical parameters from three monitoring stations (S1, S2 and S3) was collected from 1989 to 2007 and from an other three stations (S4, S5 and S6) during the period of 1999–2007. A one-way ANOVA was employed to evaluate the spatial variation of water quality for each station. The results showed that there were statistically significant spatial differences for most water quality parameters except temperature and dissolved oxygen in the entire reservoir, and the concentrations of most parameters were higher in the uppermost part of the reservoir. The temporal trend study was conducted using the Seasonal–Kendall's test. The results revealed improving trends of water quality from 1989 to 2007, including a reduction of total phosphorous, temperature and biochemical oxygen demand and an increase of dissolved oxygen. High N:P ratios, ranging from 52.61 to 78.75, indicated that the reservoir was a phosphorous-limited environment. This study suggests long-term spatial and temporal variations of water quality in the Yuqiao Reservoir, which could be informative for water quality managers and scientists.

scholarly journals Analysis of water quality time series for improving the measurement strategy in the Brantas basin, Indonesia

2021 ◽  
Author(s):  
Tijmen Willard ◽  
Reza Pramana ◽  
Saket Pande ◽  
Boris van Breukelen ◽  
Maurits Ertsen
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Hot Spots ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Water Levels ◽  
Quality Data ◽  
Data Sets ◽  
Water Quality Data ◽  
Box Plots

<p>Water quality in the rivers and tributaries of the Brantas catchment (about 12.000 km<sup>2</sup>; East Java, Indonesia), which is deteriorating due to various reasons, is measured by different agencies involved in water resource development and management. We discuss how different time series of water quality data from three local agencies in the Brantas basin (differing in specific parameters and measurement frequency) have been used to provide recommendations on the improvement of (using) the different measurement strategies (in policy recommendations). In general, monthly to quarterly data were available from 2009 until 2019 at 104 locations. Data were analyzed with Principal Component Analysis (PCA) to show which parameters vary significantly across the catchment. Preliminary results suggested how parameters were related, based on series of box plots of the PCA scores. This provided insights on the first order processes that control the physical-chemical status of the Brantas River, of each agency and for all the data sets combined. Applying Python and QGIS to separate the parameters and map the hot spots in terms of eigen functions allowed relating water levels with hot spots to estimate the fluctuations in the concentrations of different parameters in time and space. These data elaborations allow improving the different measurement campaigns, and to address specific policy questions related to water quality monitoring more efficiently.</p>

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

2021 ◽  
Vol 10 (1) ◽  
pp. 83-98
Author(s):  
Chandra Sekhar Matli ◽  
Nivedita
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Water Quality Management ◽  
Surface Water Quality ◽  
Principal Component ◽  
Quality Data ◽  
Multivariate Statistical ◽  
Water Quality Data ◽  
Sampling Locations ◽  
Statistical Approaches

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.

scholarly journals Discovering Water Quality Changes and Patterns of the Endangered Thi Vai Estuary in Southern Vietnam through Trend and Multivariate Analysis

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1330
Author(s):  
Malte Lorenz ◽  
Hong Quan Nguyen ◽  
Trong Dieu Hien Le ◽  
Stephanie Zeunert ◽  
Duc Huy Dang ◽  
...  
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Pollution Abatement ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Rapid Improvement ◽  
Water Quality Data ◽  
Southern Vietnam

Temporal and spatial water quality data are essential to evaluate human health risks. Understanding the interlinking variations between water quality and socio-economic development is the key for integrated pollution management. In this study, we applied several multivariate approaches, including trend analysis, cluster analysis, and principal component analysis, to a 15-year dataset of water quality monitoring (1999 to 2013) in the Thi Vai estuary, Southern Vietnam. We discovered a rapid improvement for most of the considered water quality parameters (e.g., DO, NH4, and BOD) by step trend analysis, after the pollution abatement in 2008. Nevertheless, the nitrate concentration increased significantly at the upper and middle parts and decreased at the lower part of the estuary. Principal component (PC) analysis indicates that nowadays the water quality of the Thi Vai is influenced by point and diffuse pollution. The first PC represents soil erosion and stormwater loads in the catchment (TSS, PO4, and Fetotal); the second PC (DO, NO2, and NO3) determines the influence of DO on nitrification and denitrification; and the third PC (pH and NH4) determines point source pollution and dilution by seawater. Therefore, this study demonstrated the need for stricter pollution abatement strategies to restore and to manage the water quality of the Thi Vai Estuary.

Objectives of a Water Quality Monitoring Programme for the International River Basins in a Developing Country in Southern Africa – Mozambique

1984 ◽  
Vol 16 (5-7) ◽  
pp. 33-39
Author(s):  
S J Hugman
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Industrial Development ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Sample Collection ◽  
Water Quality Data ◽  
Maximum Benefit ◽  
Management And Development ◽  
International Obligations

Mozambique lies on the south-east coast of Africa. Its Independence, in 1975, was particularly difficult and severely disrupted the economy. All its major rivers rise in neighbouring countries and several, in particular those from South Africa and Swaziland, are already heavily used before crossing the border. Since 1977 the National Water Directorate has been responsible for management and development of water resources. The Directorate includes a hydrology department which maintains field-teams throughout the country. Virtually no water quality data are available from before 1972, when irregular sample collection began. Since Independence, sampling has continued but the Directorate has redefined the objectives of the programme to obtain maximum benefit from very limited resources. These objectives were chosen for economic, hydrological and political reasons. The long-term objectives are to provide the data required for agricultural and industrial development projects, to manage and maintain the quality of Mozambique's water resources, and to meet international obligations. In practice, the capacity of the hydrological service is insufficient to meet these objectives. The targets for the existing programme were therefore chosen to satisfy the most important objectives and to be feasible with present resources. The routine programme is being completely operated by technicians who have no more than nine years schooling.

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

1997 ◽  
Vol 35 (11-12) ◽  
pp. 325-331 ◽  
Author(s):  
S. A. Anderson ◽  
S. J. Turner ◽  
G. D. Lewis
Keyword(s):  
Water Quality ◽  
New Zealand ◽  
Water Quality Monitoring ◽  
Epidemiological Studies ◽  
High Ratio ◽  
Quality Data ◽  
Considerable Proportion ◽  
Multiple Sources ◽  
Water Quality Data ◽  
Bathing Water Quality

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.

scholarly journals Monitoring surface water quality using social media in the context of citizen science

2017 ◽  
Vol 21 (2) ◽  
pp. 949-961 ◽  
Author(s):  
Hang Zheng ◽  
Yang Hong ◽  
Di Long ◽  
Hua Jing
Keyword(s):  
Water Quality ◽  
Social Media ◽  
Surface Water ◽  
Surface Water Quality ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Quality Data ◽  
Future Research ◽  
Water Quality Data ◽  
Essential Information

Abstract. Surface water quality monitoring (SWQM) provides essential information for water environmental protection. However, SWQM is costly and limited in terms of equipment and sites. The global popularity of social media and intelligent mobile devices with GPS and photography functions allows citizens to monitor surface water quality. This study aims to propose a method for SWQM using social media platforms. Specifically, a WeChat-based application platform is built to collect water quality reports from volunteers, which have been proven valuable for water quality monitoring. The methods for data screening and volunteer recruitment are discussed based on the collected reports. The proposed methods provide a framework for collecting water quality data from citizens and offer a primary foundation for big data analysis in future research.

scholarly journals The impact of conifer harvesting on stream water quality: the Afon Hafren, mid-Wales

2004 ◽  
Vol 8 (3) ◽  
pp. 503-520 ◽  
Author(s):  
C. Neal ◽  
B. Reynolds ◽  
M. Neal ◽  
H. Wickham ◽  
L. Hill ◽  
...  
Keyword(s):  
Water Quality ◽  
Stream Water ◽  
Strong Support ◽  
Shallow Groundwater ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Stream Water Quality ◽  
Catchment Scale ◽  
Water Quality Data ◽  
The Impact

Abstract. Results for long term water quality monitoring are described for the headwaters of the principal headwater stream of the River Severn, the Afon Hafren. The results are linked to within-catchment information to describe the influence of conifer harvesting on stream and shallow groundwater quality. A 19-year record of water quality data for the Hafren (a partially spruce forested catchment with podzolic soil) shows the classic patterns of hydrochemical change in relation to concentration and flow responses for upland forested systems. Progressive felling of almost two-thirds of the forest over the period of study resulted in little impact from harvesting and replanting in relation to stream water quality. However, at the local scale, a six years’ study of felling indicated significant release of nitrate into both surface and groundwater; this persisted for two or three years before declining. The study has shown two important features. Firstly, phased felling has led to minimal impacts on stream water. This contrasts with the results of an experimental clear fell for the adjacent catchment of the Afon Hore where a distinct water quality deterioration was observed for a few years. Secondly, there are localised zones with varying hydrology that link to groundwater sources with fracture flow properties. This variability makes extrapolation to the catchment scale difficult without very extensive monitoring. The implications of these findings are discussed in relation to strong support for the use of phased felling-based management of catchments and the complexities of within catchment processes. Keywords: deforestation, water quality, acidification, pH, nitrate, alkalinity, ANC, aluminium, dissolved organic carbon, Plynlimon, forest, spruce, Afon Hafren, podzol

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