scholarly journals Pengenalan Makroinvertebrata Bentik sebagai Bioindikator Pencemaran Perairan Sungai pada Siswa di Wonosalam, Mojokerto, Jawa Timur

2019 ◽  
Vol 5 (3) ◽  
pp. 210-215
Author(s):  
Nirmala Fitria Firdhausi
Keyword(s):  
Water Quality ◽  
Benthic Macroinvertebrates ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Monitoring Methods ◽  
Identification Process ◽  
Sampling Process ◽  
Main Target ◽  
Area Monitoring

The river in Wonosalam is upstream of the rivers that flow in the Mojokerto and Jombang regions. As an upstream area, monitoring water quality of the river is needed so that pollution can be detected early. Water quality monitoring activities can be carried out using benthic macroinvertebrates indicator. The purpose of this PKM activity was to introduce water quality monitoring methods used benthic macroinvertebrates as bioindicators for students in the Wonosalam sub-district area. The main target of this activity is students of SLTPN 1 Wonosalam. The method used was lecturing, direct practicing, and discussion. Introduction of the benthic macroinvertebrates as a bioindicator was carried out very well: the students were very enthusiastic in the implementation activities from beginning to end, the students were quite active in the sampling process until the identification process, there was an increase in the students knowledge about bioindicators and the students were able to distinguish groups, EPT (Ephemeroptera, Plecoptera, and Trichoptera) and non-EPT. Based on benthic macroinvertebrate sampling the result showed that the value of the Sumber Bengawan river are 6.25, indicated that Sumber Bengawan river was not polluted.

scholarly journals Discussion on Quality Monitoring of Water by Wireless Sensor Networks

2019 ◽  
Vol 9 (2S3) ◽  
pp. 337-341
Keyword(s):  
Water Quality ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Monitoring Methods ◽  
Main Aspect ◽  
Quality Of Water ◽  
Human Need ◽  
Area Monitoring ◽  
Monitoring Quality

Water quality is one of the main aspect to control health and the state of diseases in people. Disorder akin to unstable water conditions have over 300 collection cases announced annually. Water quality is a measure of the plight of water aunt to any human need. Basin and estuary are the cable authority of drinking water, angling, flooding, and efficiency production, which appreciably depend on water aspect. Therefore, water aspect of basin and estuary should be kept at a certain level. This paper surveys the utilization of WSN in environmental monitoring and area monitoring, with particular attention on water quality. Various WSN based water quality monitoring methods advised by other composer are considered and evaluate, taking into account their coverage, energy and security involvement. In this paper we surveys the issues of quality monitoring of water and surveys the various sensors used for monitoring quality of water

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 Field Spectroscopy as a Tool for Enhancing Water Quality Monitoring in the ACE Basin, SC

2017 ◽  
pp. 41-55 ◽  
Author(s):  
Caitlyn C. Mayer ◽  
Khalid A. Ali
Keyword(s):  
Water Quality ◽  
South Carolina ◽  
Chlorophyll A ◽  
Algal Species ◽  
Water Quality Monitoring ◽  
Water Systems ◽  
Quality Monitoring ◽  
Least Squares Regression ◽  
Monitoring Methods

The Ashepoo, Combahee, Edisto (ACE) Basin in South Carolina is one of the largest undeveloped estuaries in the Southeastern United States. This system is monitored and protected by several government agencies to ensure its health and preservation. However, as populations in surrounding cities rapidly expand and land is urbanized, the surrounding water systems may decline from an influx of contaminants, leading to hypoxia, fish kills, and eutrophication. Conventional in situ water quality monitoring methods are timely and costly. Satellite remote sensing methods are used globally to monitor water systems and can produce an instantaneous synopsis of color-producing agents (CPAs), including chlorophyll-a, suspended matter (TSM), and colored-dissolved organic matter by applying bio-optical models. In this study, field, laboratory, and historical land use land cover (LULC) data were collected during the summers of 2002, 2011, 2015, and 2016. The results indicated higher levels of chlorophyll, ranging from 2.94 to 12.19 μg/L, and TSM values were from 60.4 to 155.2 mg/L between field seasons, with values increasing with time. A model was developed using multivariate, partial least squares regression (PLSR) to identify wavelengths that are more sensitive to chlorophyll-a (R2 = 0.49; RMSE = 1.8 μg/L) and TSM (R2 = 0.40; RMSE = 12.9 mg/L). The imbrication of absorption and reflectance features characterizing sediments and algal species in ACE Basin waters make it difficult for remote sensors to distinguish variations among in situ concentrations. The results from this study provide a strong foundation for the future of water quality monitoring and for the protection of biodiversity in the ACE basin.

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 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 GSM Based Water Quality Monitoring System Using Arduino

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.

Wetland Ecosystem Monitoring Through Water Quality Perspectives

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.

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

Water ◽  
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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