Problems Associated with Particulate Matter in Water Reuse for Agricultural Irrigation and Their Prevention

1986 ◽  
Vol 18 (9) ◽  
pp. 185-195 ◽  
Author(s):  
A. Adin
Keyword(s):  
Water Quality ◽  
Drip Irrigation ◽  
Distribution System ◽  
Water Reuse ◽  
Sprinkler Irrigation ◽  
Water Quality Monitoring ◽  
Chemical Precipitation ◽  
Surface Irrigation ◽  
Irrigation Systems

Methods of irrigation are reviewed, including surface irrigation, sprinkler irrigation and drip irrigation, and the problems of these systems with regard to the quality of the water used are described. Surface irrigation does not suffer much from water quality problems, but both sprinkler irrigation and drip irrigation systems are more affected, the main problem being clogging of pumps, pipes and orifices. Clogging is usually due to a combination of suspended matter, chemical precipitation and biological growth. Current solutions through water treatment, and associated problems with this, are described, with examples given of typical strainers and filters. The key to the solution of clogging problems is a proper match between water quality of the source and within the distribution system, and the type ot treatment to be used, therefore, proper water quality monitoring is recommended. Direct granular filtration is the most preferaDle treatment process for drip irrigation systems.

Statistical and Data Mining Techniques for Understanding Water Quality Profiles in a Mining-Affected River Basin

2018 ◽  
Vol 9 (2) ◽  
pp. 1-19 ◽  
Author(s):  
Jose Simmonds ◽  
Juan A. Gómez ◽  
Agapito Ledezma
Keyword(s):  
Data Mining ◽  
Water Quality ◽  
River Basin ◽  
Suspended Solids ◽  
Water Quality Monitoring ◽  
High Flow ◽  
Quality Monitoring ◽  
Low Flow ◽  
Inverse Relation

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.

scholarly journals Analysis Quality of Water River and Quality of Well Water in The Surrounding of Rejo Agung Baru Sugar Factory Madiun

2018 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Susanti Oktavia Ningrum
Keyword(s):  
Water Quality ◽  
Agricultural Waste ◽  
Water Quality Management ◽  
Domestic Wastewater ◽  
Quality Standards ◽  
Water Quality Monitoring ◽  
Well Water ◽  
Sugar Factory ◽  
Quality Of Water

The quality of wastewater sugar factory produced will affect the environmental health quality around the factory. The study aimed to analyze the quality of water river and the quality of wells around the Rejo Agung Baru sugar factory in the Madiun. This study is an descriptive observational. The samples comprised of 5 sampels of water rivers and 7 samples of well water. The results of the study at the quality of water river showed that there are parameters (BOD5 and temperature) unqualified with the quality standards based on the East Java Regional Regulation No. 2 of 2008 about Water Quality Management and Water Pollution Control in the East Java, the quality of water river is also affected by the waste water, trash, agricultural waste, and other pollutants. The result of measuring the quality of water well showed that there are parameters (organic substance) unqualified with quality standards based on Permenkes No: 416/Menkes/PER/ IX/1990 about the Terms and Water Quality Monitoring, the quality of Well water is also affected by the quality of water river, a distance of toilet, domestic wastewater and other pollutants. The quality of water river and the quality of well water have decreased that required supervision on the quality of a river water and the quality of water of a well.

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 Water quality event detection and customer complaint clustering analysis in distribution systems

2012 ◽  
Vol 12 (5) ◽  
pp. 580-587 ◽  
Author(s):  
Stephen Mounce ◽  
John Machell ◽  
Joby Boxall
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Source ◽  
Water Quality Monitoring ◽  
Water Utility ◽  
Drinking Water Distribution ◽  
Historic Data

Safe, clean drinking water is a foundation of society and water quality monitoring can contribute to ensuring this. A case study application of the CANARY software to historic data from a UK drinking water distribution system is described. Sensitivity studies explored appropriate choice of algorithmic parameter settings for a baseline site, performance was evaluated with artificial events and the system then transferred to all sites. Results are presented for analysis of nine water quality sensors measuring six parameters and deployed in three connected district meter areas (DMAs), fed from a single water source (service reservoir), for a 1 year period and evaluated using comprehensive water utility records with 86% of event clusters successfully correlated to causes (spatially limited to DMA level). False negatives, defined by temporal clusters of water quality complaints in the pilot area not corresponding to detections, were only approximately 25%. It was demonstrated that the software could be configured and applied retrospectively (with potential for future near real time application) to detect various water quality event types (with a wider remit than contamination alone) for further interpretation.

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

2019 ◽  
Vol 10 (1) ◽  
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.

scholarly journals Antibiotics in WWTP discharge into the Chaobai River, Beijing

2016 ◽  
Vol 42 (4) ◽  
pp. 48-57 ◽  
Author(s):  
Zhang Chunhui ◽  
Wang Liangliang ◽  
Gao Xiangyu ◽  
He Xudan
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Treatment Plant ◽  
Water Quality Monitoring ◽  
Environmental Distribution ◽  
Receiving River ◽  
Dominant Point ◽  
Aerated Filter ◽  
Beijing China

Abstract22 representative antibiotics, including 8 quinolones (QNs), 9 sulfonamides (SAs), and 5 macrolides (MCs) were selected to investigate their occurrence and removal efficiencies in a Wastewater Treatment Plant (WWTP) and their distribution in the receiving water of the Chaobai River in Beijing, China. Water quality monitoring was performed in an integrated way at different selected points in the WWTP to explore the potential mechanism of antibiotics removal during wastewater treatment. Water quality of the Chaobai River was also analyzed to examine environmental distribution in a river ecosystem. The results showed that within all the 22 compounds examined, 10 antibiotics were quantified in wastewater influent, 10 in effluent, and 7 in river. Sulfadiazine (SDZ, 396 ng/L) and Sulfamethazine (SMZ, 382 ng/L) were the dominating antibiotics in the influent. Both the conventional treatment and advanced Biological Aerated Filter (BAF) system was important for the removal of antibiotics from the wastewater. And the concentrations of selected antibiotics were ranged from 0-41.8 ng/L in the effluent-receiving river. Despite the fact that the concentrations were reduced more than 50% compared to effluent concentrations, WWTP discharge was still regarded as a dominant point-source input of antibiotics into the Chaobai River.

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