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

scholarly journals An Observational Process Ontology-Based Modeling Approach for Water Quality Monitoring

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 715
Author(s):  
Xiaolei Wang ◽  
Haitao Wei ◽  
Nengcheng Chen ◽  
Xiaohui He ◽  
Zhihui Tian
Keyword(s):  
Water Quality ◽  
Water Quality Monitoring ◽  
Process Models ◽  
Quality Monitoring ◽  
Quality Data ◽  
Observation Data ◽  
Process Ontology ◽  
Water Quality Data ◽  
Data Process ◽  
Monitoring Process

The increasing deterioration of aquatic environments has attracted more attention to water quality monitoring techniques, with most researchers focusing on the acquisition and assessment of water quality data, but seldom on the discovery and tracing of pollution sources. In this study, a semantic-enhanced modeling method for ontology modeling and rules building is proposed, which can be used for river water quality monitoring and relevant data observation processing. The observational process ontology (OPO) method can describe the semantic properties of water resources and observation data. In addition, it can provide the semantic relevance among the different concepts involved in the observational process of water quality monitoring. A pollution alert can be achieved using the reasoning rules for the water quality monitoring stations. In this study, a case is made for the usability testing of the OPO models and reasoning rules by utilizing a water quality monitoring system. The system contributes to the water quality observational monitoring process and traces the source of pollutants using sensors, observation data, process models, and observation products that users can access in a timely manner.

scholarly journals A Low-Cost Water Quality Monitoring System for the Ayeyarwady River in Myanmar Using a Participatory Approach

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1984 ◽  
Author(s):  
Thanda Thatoe Nwe Win ◽  
Thom Bogaard ◽  
Nick van de Giesen
Keyword(s):  
Water Quality ◽  
Mobile Phone ◽  
Low Cost ◽  
School Teacher ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Quality Data ◽  
Water Quality Data ◽  
Lower Accuracy

Newly developed mobile phone applications in combination with citizen science are used in different fields of research, such as public health monitoring, environmental monitoring, precipitation monitoring, noise pollution measurement and mapping, earth observation. In this paper, we present a low-cost water quality mobile phone measurement technique combined with sensor and test strips, and reported the weekly-collected data of three years of the Ayeyarwady River system by volunteers at seven locations and compared these results with the measurements collected by the lab technicians. We assessed the quality of the collected data and their reliability based on several indicators, such as data accuracy, consistency, and completeness. In this study, six local governmental staffs and one middle school teacher collected baseline water quality data with high temporal and spatial resolution. The quality of the data collected by volunteers was comparable to the data of the experienced lab technicians for sensor-based measurement of electrical conductivity and transparency. However, the lower accuracy (higher uncertainty range) of the indicator strips made them less useful in the Ayeyarwady with its relatively small water quality variations. We showed that participatory water quality monitoring in Myanmar can be a serious alternative for a more classical water sampling and lab analysis-based monitoring network, particularly as it results in much higher spatial and temporal resolution of water quality information against the very modest investment and running costs. This approach can help solving the invisible water crisis of unknown water quality (changes) in river and lake systems all over the world.

scholarly journals Clustering of Time Series Water Quality Data Using Dynamic Time Warping: A Case Study from the Bukhan River Water Quality Monitoring Network

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2411
Author(s):  
Seulbi Lee ◽  
Jaehoon Kim ◽  
Jongyeon Hwang ◽  
EunJi Lee ◽  
Kyoung-Jin Lee ◽  
...  
Keyword(s):  
Water Quality ◽  
River Water ◽  
Monitoring Network ◽  
Water Quality Monitoring ◽  
Euclidean Algorithm ◽  
Quality Monitoring ◽  
Quality Data ◽  
Time Warping ◽  
Water Quality Data ◽  
Dynamic Time

It is essential to monitor water quality for river water management because river water is used for various purposes and is directly related to the health and safety of a population. Proper network installation and removal is an important part of water quality monitoring and network operation efficiency. To do this, cluster analysis based on calculated similarity between measuring stations can be used. In this study, we measured the similarities between 12 water quality monitoring stations of the Bukhan River. River water quality data always have a station-dependent time lag because water flows from upstream to downstream; therefore, we proposed a Dynamic Time Warping (DTW) algorithm that searches for the minimum distance by changing and comparing time-points, rather than using the Euclidean algorithm, which compares the same time-point. Both Euclidean and DTW algorithms were applied to nine water quality variables to identify similarities between stations, and K-medoids cluster analysis were performed based on the similarity. The Clustering Validation Index (CVI) was used to select the optimal number of clusters. Our results show that the Euclidean algorithm formed clusters by mixing mainstream and tributary stations; the mainstream stations were largely divided into three different clusters. In contrast, the DTW algorithm formed clear clusters by reflecting the characteristics of water quality and watershed. Furthermore, because the Euclidean algorithm requires the lengths of the time series to be the same, data loss was inevitable. As a result, even where clusters were the same as those obtained by DTW, the characteristics of the water quality variables in the cluster differed. The DTW analysis in this study provides useful information for understanding the similarity or difference in water parameter values between different locations. Thus, the number and location of required monitoring stations can be adjusted to improve the efficiency of field monitoring network management.

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.

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