scholarly journals Integration of sensors for dam water quality analysis – a prototype

2021 ◽  
Author(s):  
Lina Rose ◽  
X. Anitha Mary ◽  
C. Karthik
Keyword(s):  
Water Quality ◽  
Pure Water ◽  
Quality Parameters ◽  
Water Bodies ◽  
Quality Analysis ◽  
Quality Data ◽  
Major Portion ◽  
Water Quality Analysis ◽  
Water Quality Control ◽  
Water Quality Data

Abstract Water consumed is stored in several water bodies in and around us, out of which dams accommodate a major portion of water. The quantity and quality monitoring of water in Dams is troublesome due to its large surface area and high depths. Though groundwater resources are the primary water source in India, Dams plays a vital role in water distribution and storage network. Central Water Commission in India has identified more than 5,000 dams of which a major portion is persistently consumed by the rural and urban population for drinking and irrigation. The water quality of these reservoirs is of serious concern as it would not only affect the socio-economic status of the nation but the aquatic systems as well. Water quality control and management are vital for delivering clean water supply to the common society. Because of their size, collecting, assessing, and managing a vast volume of water quality data is critical. Water quality data is primarily obtained through manual field sampling; however, real-time sensor monitoring is increasingly being used for more efficient data collection. The literature depicts that the methodsinvolving remote sensing and image processing of water quality analysis consume time, require sample collection at various depths, analysis of collected samples, and manual interpretations. The objective of this study is to propose a novel cost-effective method to monitor water quality devoid of considerable human intervention. The sensor-based online monitoring aids in assessing the sample with limited technology, at various depths of water in the dam to analyze turbidity which gives the major indication of pure water. The quality analysis of the dam water is worthy if the water is assessed at the distribution end before consumption. Hence, to enhance the water management system, other quality parameters like pH, conductivity, temperature are sensed and monitored in the distribution pipeline. The unstable pH can alter the chemical and microbiological aspects of water resulting in a variation of other water quality parameters Temperature variations affect the amount of dissolved oxygen in the water bodies which results in unstable quality parameters. The change in dissolved solvents and the ionic concentration alters the electrical conductivity of the water and the increased concentration of salts also results in turbidity. The data from all the sensors are processed by the microcontroller, transmitted, and displayed in a mobile application comprehensible to the layman.

Assessement of Water Quality Parameters in Some Potential Pollutant Areas from Romania

2018 ◽  
Vol 69 (8) ◽  
pp. 2045-2049
Author(s):  
Catalina Gabriela Gheorghe ◽  
Andreea Bondarev ◽  
Ion Onutu
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Chemical Parameters ◽  
Water Quality Data ◽  
Pollutant Sources ◽  
Water Quality Forecasting

Monitoring of environmental factors allows the achievement of some important objectives regarding water quality, forecasting, warning and intervention. The aim of this paper is to investigate water quality parameters in some potential pollutant sources from northern, southern and east-southern areas of Romania. Surface water quality data for some selected chemical parameters were collected and analyzed at different points from March to May 2017.

Development of Dialog System Model for Eutrophication Control between Discharging River Basin and Receiving Water Body – Case Study of Lake Sagami (Japan)

1989 ◽  
Vol 21 (12) ◽  
pp. 1821-1824
Author(s):  
M. Suzuki ◽  
K. Chihara ◽  
M. Okada ◽  
H. Kawashima ◽  
S. Hoshino
Keyword(s):  
Water Management ◽  
Water Quality ◽  
Expert System ◽  
River Basin ◽  
Water Body ◽  
Water Bodies ◽  
Quality Data ◽  
Pollution Load ◽  
Water Quality Data ◽  
Receiving Water

A computer program based on expert system software was developed and proposed as a prototype model for water management to control eutrophication problems in receiving water bodies (Suzuki etal., 1988). The system has several expert functions: 1. data input and estimation of pollution load generated and discharged in the river watershed; 2. estimation of pollution load run-off entering rivers; 3. estimation of water quality of receiving water bodies, such as lakes; and 4. assisting man-machine dialog operation. The program can be used with MS-DOS BASIC and assembler in a 16 bit personal computer. Five spread sheets are utilized in calculation and summation of the pollutant load, using multi-windows. Partial differential equations for an ecological model for simulation of self-purification in shallow rivers and simulation of seasonal variations of water quality in a lake were converted to computer programs and included in the expert system. The simulated results of water quality are shown on the monitor graphically. In this study, the expert system thus developed was used to estimate the present state of one typical polluted river basin. The river was the Katsura, which flows into Lake Sagami, a lake dammed for water supply. Data which had been actually measured were compared with the simulated water quality data, and good agreement was found. This type of expert system is expected to be useful for water management of a closed water body.

scholarly journals Dampak Limbah Penambangan Emas Tanpa Izin (Peti) Terhadap Kualitas Air Sungai Limun Kabupaten Sarolangun Propinsi Jambi - The Impact Of Illegal Gold Mining Activity To The Water Quality Of Limun River, Sarolangun District, Jambi Province

2017 ◽  
Vol 14 (3) ◽  
pp. 251
Author(s):  
Rita Yulianti ◽  
Emi Sukiyah ◽  
Nana Sulaksana
Keyword(s):  
Water Quality ◽  
Gold Mining ◽  
Quality Standard ◽  
Water Levels ◽  
Quality Analysis ◽  
Quality Data ◽  
Mining Activities ◽  
Water Quality Data ◽  
The Impact

Daerah penelitian terletak di desa Muaro Limun, Kecamatan Limun Kabupaten Sarolangun Provinsi Jambi. Sungai limun, salah satu sungai besar di daerah kabupaten sarolangun yang dimanfaatkan oleh mayarakat sekitarnya sebagai sumber penghidupan. Penelitian bertujuan untuk mengetahui pengaruh kegiatan penambangan terhadap kualitas air sungai Batang Limun, dan perubahan sifat fisik dan  kimia yang diakibatkan   kegiatan penambangan.Metode yang digunakan adalah  metode grab sampel, serta stream sedimen untuk dianalis di laboratorium. Sejumlah sampel diambil di beberapa lokasi Penambangan Emas berdasarkan Aliran Sub-DAS dan dibandingkan dengan beberapa sampel lain yang diambil pada lokasi yang belum terkontaminasi oleh kegiatan penambangan. Analisis kualitas air mengacu pada  SMEWWke 22 tahun 2012 dan standar baku mutu air kelas II dalam PP No 82 yang dikeluarkan oleh Menteri Kesehatan No. 492/Menkes/Per/IV/2010. Diketahui sungai Batang Limun telah mengalami perubahan karakteristik fisika dan kimia. Dari grafik  kosentrasi kekeruhan, pH, TSS, TDS  Cu, Pb, Zn, Mn, Hg terlihat bahwa penambang emas tanpa izin (PETI) dengan cara amalgamasi yang menyebabkan terjadinya penurunan kualitas air sungai. Sejak tahun 2009 sampai tahun 2015  sungai Limun dan sekitarnya terus mengalami penurunan kualitas air. Penurunan kualitas yang cukup tinggi terjadi  yaitu peningkatan nilai Rata-rata konsentrasi merkuri pada sungai Batang Limun dari 0,18ppb (0,00018 mg/l)  menjadi 0,3ppb (0,0003 mg/l), peningkatan tersebut dipengaruhi oleh proses kegiatan penambangan dan nilai tersebut masih dibawah standar baku mutu air kelas II  pp nomor 82 tahun 2010.Kata kunci :   Kualitas Air, Sungai Limun,TSS, Merkuri, PETI Limun river is one of the major rivers in the area of Sarolangun, which utilized by the society as a source of livelihood. The aim of study  to analyze the effect of mining activities on  the water quality of Batang Limun River, and the changes of physical and chemical properties of water. The method used are grab  and stream samples to  sediment analyzed in the laboratory. A number of samples were taken at several locations based Flow Gold Mining Sub-watershed and compared to some other samples taken at the location that has not been contaminated by mining activities. Water quality analysis referring to SMEWW, 22nd edition 2012 and refers to Regulation No 82 that issued by Minister of Health No. 492 / Menkes / Per / IV / 2010.The results showed that the Limun river has undergone chemical changes in physical characteristics. These symptoms can be seen from the discoloration of clear water in the river before the mine becomes brownish after mining, based on graphic of muddiness concentration: pH, TSS, TDS Cu, Pb, Zn, Mn, Hg have seen that  the illegal miner which used amalgamation caused deterioration in water quality, data from 2009 to 2015 Limun river and surrounding areas continue to experience a decrease in water quality. The decreasing of water quality showed in the TSS parameter which found in the area is to high based on  the standard of water quality class II pp number 82 of 2010. An increase in the value of average concentrations of mercury in the Batang Limun river before mine 0,18ppb (0.00018 mg / l) into 0,3ppb (0.0003 mg / l) on the river after the mine. The increase was affected by the mining activities and the value is still below the air quality standard Grade II pp numbers 82 years 2010, although the value is still below with the standards quality standard, the mercury levels in water should still be a major concern because if it accumulates continuously in the water levels will increase and will be bad for health. In contrast to the concentration of mercury in sediments that have a higher value is 153 ppb (0,513ppm ) .Key Words :   Water Quality, Limun River, Mercury, Illegal gold mining

scholarly journals Chemometric analysis of drinking water quality parameters of Sagar city, Madhya Pradesh, India

2020 ◽  
Vol 31 (2) ◽  
pp. 99-105
Author(s):  
Hemant Pathak
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Quality Parameters ◽  
Chemometric Analysis ◽  
Madhya Pradesh ◽  
Drinking Water Quality ◽  
Quality Data ◽  
Multivariate Linear Regression Analysis ◽  
Water Quality Data ◽  
Entire Study

AbstractThe present study uses numerous chemometric techniques to evaluate and interpret a water quality data obtained from the drinking water resources namely municipal water (supplied by Rajghat dam on Bewas River), bore well, ground water of Sagar city, a divisional headquarter of Madhya Pradesh, India. Data was collected from May 2018 to June 2019 for 10 parameters used to assess the status of the water quality. Water quality was monitored at 15 sampling stations along the entire district. The data were analyzed using chemometric analysis such as principal component analysis, correlation matrix, multivariate linear regression analysis and hierarchical cluster analysis that reduced the data dimensions for better interpretation. Results of statistical analysis expressed that slightly higher value of BOD in some areas due to sewage contamination, need of chlorination treatment required at those places. This study also presents the value of diverse statistical methods for assessment and analysis of drinking water quality data for the reason of monitoring the effectiveness of water resource management. The study indicated that the maximum quality parameters of drinking water is in permissible limits of WHO and IS: 10500 guidelines on entire study places.

scholarly journals THE CONTRIBUTION OF GIS TO DISPLAY AND ANALYZE THE WATER QUALITY DATA COLLECTED BY A WIRELESS SENSOR NETWORK: CASE OF BOUREGREG CATCHMENT, MOROCCO

2017 ◽  
Vol IV-4/W4 ◽  
pp. 331-334
Author(s):  
S. Boubakri ◽  
H. Rhinane
Keyword(s):  
Water Quality ◽  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Geographic Information Systems ◽  
Real Time ◽  
Quality Parameters ◽  
Wireless Sensor ◽  
Quality Data ◽  
Catchment Scale ◽  
Water Quality Data

The monitoring of water quality is, in most cases, managed in the laboratory and not on real time bases. Besides this process being lengthy, it doesn’t provide the required specifications to describe the evolution of the quality parameters that are of interest. This study presents the integration of Geographic Information Systems (GIS) with wireless sensor networks (WSN) aiming to create a system able to detect the parameters like temperature, salinity and conductivity in a Moroccan catchment scale and transmit information to the support station. This Information is displayed and evaluated in a GIS using maps and spatial dashboard to monitor the water quality in real time.

In-line river monitoring – new challenges and opportunities

2004 ◽  
Vol 50 (11) ◽  
pp. 67-72 ◽  
Author(s):  
A. Pressl ◽  
S. Winkler ◽  
G. Gruber
Keyword(s):  
Water Management ◽  
Water Quality ◽  
Wastewater Treatment Plants ◽  
Indirect Measurement ◽  
Water Bodies ◽  
Danube River ◽  
Quality Data ◽  
Water Quality Data ◽  
Challenges And Opportunities ◽  
Receiving Water

Water management becomes a complex issue when considering the large number of water-rights-of-use like drinking water production, recreation, receiving water, transport on and ecological quality of the water bodies. Recent changes in the legal requirements concerning water management on European scale (EC Water Framework Directive, 2000/60/EC) highlighted the need for appropriate means for monitoring water quality and exchange of water quality data. Indirect measurement of water quality using surrogate parameters (chemical and physical-chemical parameters) can be automated at a high accuracy level. This was shown over the past years by national and international research projects. In 2001 such a research project has started in Austria focusing on the installation and operation of a pilot water quality network, which is suitable for application at several points of interest of water management, i.e. sewer networks, wastewater treatment plants and receiving water bodies. The paper describes the operational problems and experiences of collecting data over a period of one year in the Danube River downstream of Vienna. The sensors are installed in situ, directly in the river, without any bypass system. The first evaluation of the measurements shows that the values are reliable and therefore applicable to further interpretations.

Generation of geolocated and radiometrically corrected true reflectance surfaces in the visible portion of the electromagnetic spectrum over large bodies of water using images from a sUAS

2020 ◽  
Vol 8 (3) ◽  
pp. 172-185
Author(s):  
Juan G. Arango ◽  
Brandon K. Holzbauer-Schweitzer ◽  
Robert W. Nairn ◽  
Robert C. Knox
Keyword(s):  
Water Quality ◽  
Near Infrared ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Electromagnetic Spectrum ◽  
Water Quality Data ◽  
Ground Control Points ◽  
Bodies Of Water

The focus of this study was to develop true reflectance surfaces in the visible portion of the electromagnetic spectrum from small unmanned aerial system (sUAS) images obtained over large bodies of water when no ground control points were available. The goal of the research was to produce true reflectance surfaces from which reflectance values could be extracted and used to estimate optical water quality parameters utilizing limited in-situ water quality analyses. Multispectral imagery was collected using a sUAS equipped with a multispectral sensor, capable of obtaining information in the blue (0.475 μm), green (0.560 μm), red (0.668 μm), red edge (0.717 μm), and near infrared (0.840 μm) portions of the electromagnetic spectrum. To develop a reliable and repeatable protocol, a five-step methodology was implemented: (i) image and water quality data collection, (ii) image processing, (iii) reflectance extraction, (iv) statistical interpolation, and (v) data validation. Results indicate that the created protocol generates geolocated and radiometrically corrected true reflectance surfaces from sUAS missions flown over large bodies of water. Subsequently, relationships between true reflectance values and in-situ water quality parameters were developed.

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.

Reducing Cooling Tower Fill Fouling and Degradation With Water Quality Control

2007 ◽  
Author(s):  
Vickie G. Olson
Keyword(s):  
Water Quality ◽  
Quality Control ◽  
Heat Dissipation ◽  
Structural Integrity ◽  
Cooling Tower ◽  
Quality Analysis ◽  
Water Quality Analysis ◽  
Water Quality Control ◽  
Side Stream ◽  
And Control

Cooling tower fill may be composed of wood or plastic, but it must provide adequate surface area for heat dissipation. Online and field water quality analysis can maximize tower efficiency and minimize maintenance. Uncontrolled levels of pH, bio-growth, or over-application of chemicals cause degradation of the material and plugging. Automatic control of pH conditioner can be accomplished with proven differential pH methods tied to analog and/or digital control. Oxidizing biocide application can be optimized with ORP and halogen analysis and control. Overuse of this type of biocide can also cause wood delignification that can affect the structural integrity of the tower. Another cause of fouling is excessive solids accumulation. Solids buildup can be minimized with side-stream filtration and/or clarification and monitored with low maintenance self-cleaning optical probes.

scholarly journals GRQA: Global River Water Quality Archive

2021 ◽  
Author(s):  
Holger Virro ◽  
Giuseppe Amatulli ◽  
Alexander Kmoch ◽  
Longzhu Shen ◽  
Evelyn Uuemaa
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Quality Measurement ◽  
Observation Time ◽  
Quality Analysis ◽  
Quality Data ◽  
Observation Data ◽  
Water Quality Data ◽  
Spatial Coverage ◽  
Global Datasets

Abstract. A major problem related to global water quality analysis and modelling has been the lack of available good quality and consistent water quality measurement datasets with a global spatial coverage. Current study aims to contribute into improving the global datasets on water quality by aggregating and harmonizing five national, continental and global datasets: CESI, GEMSTAT, GLORICH, WATERBASE and WQP. The GRQA compilation involved converting observation data from the five sources into a common format and harmonizing the corresponding metadata, flagging outliers, calculating time series characteristics and detecting duplicate observations from sources with a spatial overlap. The final dataset extends the spatial and temporal coverage of previously available water quality data and contains 42 parameters and over 16 million measurements around the globe covering the 1898–2020 time period. Metadata in the form of statistical tables, maps and figures are provided along with observation time series. The GRQA dataset, supplementary metadata and figures are available for download on the DataCite and OpenAire enabled repository of the University of Tartu, DataDOI, http://dx.doi.org/10.23673/re-273 (Virro et al., 2021).

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