Temporal variability in water quality of agricultural tailwaters: Implications for water quality monitoring

This article contains a multivariate analysis (MV), data mining (DM) techniques and water quality index (WQI) metrics which were applied to a water quality dataset from three water quality monitoring stations in the Petaquilla River Basin, Panama, to understand the environmental stress on the river and to assess the feasibility for drinking. Principal Components and Factor Analysis (PCA/FA), indicated that the factors which changed the quality of the water for the two seasons differed. During the low flow season, water quality showed to be influenced by turbidity (NTU) and total suspended solids (TSS). For the high flow season, main changes on water quality were characterized by an inverse relation of NTU and TSS with electrical conductivity (EC) and chlorides (Cl), followed by sources of agricultural pollution. To complement the MV analysis, DM techniques like cluster analysis (CA) and classification (CLA) was applied and to assess the quality of the water for drinking, a WQI.

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

Water ◽

10.3390/w11101984 ◽

2019 ◽

Vol 11 (10) ◽

pp. 1984 ◽

Cited By ~ 4

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.

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Real-time water quality monitoring through Internet of Things and ANOVA-based analysis: a case study on river Krishna

Applied Water Science ◽

10.1007/s13201-019-1111-9 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 4

Author(s):

Prasad M. Pujar ◽

Harish H. Kenchannavar ◽

Raviraj M. Kulkarni ◽

Umakant P. Kulkarni

Keyword(s):

Water Quality ◽

Internet Of Things ◽

Real Time ◽

River Basin ◽

Water Quality Monitoring ◽

Quality Parameters ◽

Quality Monitoring ◽

Quality Analysis ◽

Water Quality Analysis

AbstractIn this paper, an attempt has been made to develop a statistical model based on Internet of Things (IoT) for water quality analysis of river Krishna using different water quality parameters such as pH, conductivity, dissolved oxygen, temperature, biochemical oxygen demand, total dissolved solids and conductivity. These parameters are very important to assess the water quality of the river. The water quality data were collected from six stations of river Krishna in the state of Karnataka. River Krishna is the fourth largest river in India with approximately 1400 km of length and flows from its origin toward Bay of Bengal. In our study, we have considered only stretch of river Krishna flowing in state of Karnataka, i.e., length of about 483 km. In recent years, the mineral-rich river basin is subjected to rapid industrialization, thus polluting the river basin. The river water is bound to get polluted from various pollutants such as the urban waste water, agricultural waste and industrial waste, thus making it unusable for anthropogenic activities. The traditional manual technique that is under use is a very slow process. It requires staff to collect the water samples from the site and take them to the laboratory and then perform the analysis on various water parameters which is costly and time-consuming process. The timely information about water quality is thus unavailable to the people in the river basin area. This creates a perfect opportunity for swift real-time water quality check through analysis of water samples collected from the river Krishna. IoT is one of the ways with which real-time monitoring of water quality of river Krishna can be done in quick time. In this paper, we have emphasized on IoT-based water quality monitoring by applying the statistical analysis for the data collected from the river Krishna. One-way analysis of variance (ANOVA) and two-way ANOVA were applied for the data collected, and found that one-way ANOVA was more effective in carrying out water quality analysis. The hypotheses that are drawn using ANOVA were used for water quality analysis. Further, these analyses can be used to train the IoT system so that it can take the decision whenever there is abnormal change in the reading of any of the water quality parameters.

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GSM Based Water Quality Monitoring System Using Arduino

Shanlax International Journal of Arts, Science and Humanities ◽

10.34293/sijash.v6i4.341 ◽

2019 ◽

Vol 6 (4) ◽

pp. 22-26

Author(s):

S Gokulanathan ◽

P Manivasagam ◽

N Prabu ◽

T Venkatesh

Keyword(s):

Water Quality ◽

Monitoring System ◽

Rapid Development ◽

Water Quality Monitoring ◽

Quality Parameters ◽

Vital Role ◽

Quality Monitoring ◽

Human Society ◽

Power Efficient

This paper investigates about water quality monitoring system through a wireless sensor network. Due to the rapid development and urbanization, the quality of water is getting degrade over year by year, and it leads to water-borne diseases, and it creates a bad impact. Water plays a vital role in our human society and India 65% of the drinking water comes from underground sources, so it is mandatory to check the quality of the water. In this model used to test the water samples and through the data it analyses the quality of the water. This paper delivers a power efficient, effective solution in the domain of water quality monitoring it also provides an alarm to a remote user, if there is any deviation of water quality parameters.

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Wetland Ecosystem Monitoring Through Water Quality Perspectives

10.4018/978-1-7998-9498-8.ch004 ◽

2022 ◽

pp. 51-70

Author(s):

Shahid Ahmad Dar ◽

Sami Ullah Bhat ◽

Sajad Ahmad Dar

Keyword(s):

Water Quality ◽

Field Testing ◽

Water Quality Monitoring ◽

Quality Monitoring ◽

Physical Parameters ◽

Chemical Parameters ◽

Ecosystem Monitoring ◽

Physico Chemical

Water quality monitoring is an important tool in determining the safety and suitability of water for various desired and intended uses. The procedures involved in the evaluation of water quality are numerous and multifaceted. Therefore, taking into consideration the specific objectives of water quality monitoring, sampling design is of vital importance. Most of the physical parameters of water quality are determined via in-situ measurements using modern testing equipment/field testing kits. Although there are some good field-based sensors that are being used for evaluation of water quality, the chemical parameters traditionally are mostly analyzed through laboratory-based experiments. This chapter is aimed to offer an inclusive knowledge and insights on the importance and assessment of physico-chemical parameters that are of high priority for monitoring the water quality of wetlands.

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Optimization of Water Quality Monitoring Networks Using Metaheuristic Approaches: Moscow Region Use Case

Water ◽

10.3390/w13070888 ◽

2021 ◽

Vol 13 (7) ◽

pp. 888

Author(s):

Elizaveta Yudina ◽

Anna Petrovskaia ◽

Dmitrii Shadrin ◽

Polina Tregubova ◽

Elizaveta Chernova ◽

...

Keyword(s):

Water Quality ◽

Water Quality Monitoring ◽

Training Sample ◽

Quality Monitoring ◽

Monitoring Networks ◽

Monitoring Procedure ◽

Dataset Size ◽

Sample Set ◽

Moscow Area

Currently many countries are struggling to rationalize water quality monitoring stations which is caused by economic demand. Though this process is essential indeed, the exact elements of the system to be optimized without a subsequent quality and accuracy loss still remain obscure. Therefore, accurate historical data on groundwater pollution is required to detect and monitor considerable environmental impacts. To collect such data appropriate sampling and assessment methodologies with an optimum spatial distribution augmented should be exploited. Thus, the configuration of water monitoring sampling points and the number of the points required are now considered as a fundamental optimization challenge. The paper offers and tests metaheuristic approaches for optimization of monitoring procedure and multi-factors assessment of water quality in “New Moscow” area. It is shown that the considered algorithms allow us to reduce the size of the training sample set, so that the number of points for monitoring water quality in the area can be halved. Moreover, reducing the dataset size improved the quality of prediction by 20%. The obtained results convincingly demonstrate that the proposed algorithms dramatically decrease the total cost of analysis without dampening the quality of monitoring and could be recommended for optimization purposes.

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Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)

Water Practice & Technology ◽

10.2166/wpt.2021.020 ◽

2021 ◽

Author(s):

Kunwar Raghvendra Singh ◽

Ankit Pratim Goswami ◽

Ajay S. Kalamdhad ◽

Bimlesh Kumar

Keyword(s):

Water Quality ◽

Water Conservation ◽

Principal Component ◽

Water Quality Monitoring ◽

Pollution Sources ◽

Quality Monitoring ◽

Conservation Strategies ◽

Rapid Urbanization ◽

Monitoring Programs

Abstract Water quality monitoring programs are indispensable for developing water conservation strategies, but elucidation of large and random datasets generated in these monitoring programs has become a global challenge. Rapid urbanization, industrialization and population growth pose a threat of pollution for the surface water bodies of the Assam, state in northeastern India. This calls for strict water quality monitoring programs, which would thereby help in understanding the status of water bodies.In this study, the water quality of Baralia and Puthimari River of Assam was assessed using cluster analysis (CA), information entropy, and principal component analysis (PCA) to derive useful information from observed data. 15 sampling sites were selected for collection of samples during the period May 2016- June 2017. Collected samples were analysed for 20 physicochemical parameters. Hierarchal CA was used to classify the sampling sites in different clusters. CA grouped all the sites into 3 clusters based on observed variables. Water quality of rivers was evaluated using entropy weighted water quality index (EWQI). EWQI of rivers varied from 61.62 to 314.68. PCA was applied to recognise various pollution sources. PCA identified six principal components that elucidated 87.9% of the total variance and represented surface runoff, untreated domestic wastewater and illegally dumped municipal solid waste (MSW) as major factors affecting the water quality. This study will help policymakers and managers for making better decisions in allocating funds and determining priorities. It will also assist in effective and efficient policies for the improvement of water quality.

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WATER QUALITY MONITORING OF GROUNDWATER IN THE RESIDENTIAL SHANGRI-LÁ- GOIÂNIA NORTH AREA

Periódico Tchê Química ◽

10.52571/ptq.v12.n23.2015.54_p_23_pgs_54_65.pdf ◽

2015 ◽

Vol 12 (23) ◽

pp. 54-65

Author(s):

Ana Paula Teodoro SILVA ◽

Jaqueline Síntia PEREIRA ◽

Julio Cesar LUZINI ◽

Káryta Soares ANDRADE ◽

Paulo Cesar de Souza GUERRA ◽

...

Keyword(s):

Water Quality ◽

Environmental Control ◽

Water Quality Monitoring ◽

Underground Water ◽

Fundamental Rights ◽

Quality Monitoring ◽

The North ◽

Frequent Accompaniment ◽

True Color

The water is one human fundamental rights, however, the simple access the water doesn't guarantee the health of who consumes it, considering that if the water is not inside of the established quality patterns it can bring serious damages so much to the human, as the fauna and the flora of an area. The accomplishment of that study is justified like this for the importance of the water for the human survival, once that resource being contaminated in some way it can bring irreversible damages to the population health. The objective constituted in monitoring the water quality of the groundwater in a division into lots, Residential Shangri-Lá located in the north area of Goiânia, through analyses of environmental control. The hypothesis that orientated of this work constituted in to show that the population uses cisterns as alternative for the obtaining of water, because the population has no access to conventional water supply. For the realization of this study samples of water were collected in the residential and it was made analyses physical-chemistries (dissolved oxygen, turbidity, true color, pH and total phosphorus) and microbiological heterotrophic contamination, escherichia coli and total coliforms). It was verified with the monitoring and analyses that the underground water used Shangri-Lá in the Residential it is not in alarming levels of contamination not even for industrial activities, septic sewages or other factors, the people's health can be committed for the failures of potability of the water consumed by residents of the condominium, demonstrating like this the need of frequent accompaniment and the reevaluation of the measures of hygienic handling in these places, due to the possibilities of contamination of several orders.

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A Bayesian approach to understanding the key factors influencing temporal variability in stream water quality: a case study in the Great Barrier Reef catchments

10.5194/hess-2020-681 ◽

2021 ◽

Author(s):

Shuci Liu ◽

Dongryeol Ryu ◽

J. Anugs Webb ◽

Anna Lintern ◽

Danlu Guo ◽

...

Keyword(s):

Water Quality ◽

Great Barrier Reef ◽

Temporal Variation ◽

Temporal Variability ◽

Stream Water ◽

Water Quality Monitoring ◽

Quality Monitoring ◽

Barrier Reef ◽

Key Factors ◽

Stream Water Quality

Abstract. Stream water quality is highly variable both across space and time. Water quality monitoring programs have collected a large amount of data that provide a good basis to investigate the key drivers of spatial and temporal variability. Event-based water quality monitoring data in the Great Barrier Reef catchments in northern Australia provides an opportunity to further our understanding of water quality dynamics in sub-tropical and tropical regions. This study investigated nine water quality constituents, including sediments, nutrients and salinity, with the aim of: 1) identifying the influential environmental drivers of temporal variation in flow event concentrations; and 2) developing a modelling framework to predict the temporal variation in water quality at multiple sites simultaneously. This study used a hierarchical Bayesian model averaging framework to explore the relationship between event concentration and catchment-scale environmental variables (e.g., runoff, rainfall and groundcover conditions). Key factors affecting the temporal changes in water quality varied among constituent concentrations, as well as between catchments. Catchment rainfall and runoff affected in-stream particulate constituents, while catchment wetness and vegetation cover had more impact on dissolved nutrient concentration and salinity. In addition, in large dry catchments, antecedent catchment soil moisture and vegetation had a large influence on dissolved nutrients, which highlights the important effect of catchment hydrological connectivity on pollutant mobilisation and delivery.

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