Artificial intelligence-based monitoring system of water quality parameters for early detection of non-specific bio-contamination in water distribution systems

2019 ◽  
Vol 19 (6) ◽  
pp. 1785-1792 ◽  
Author(s):  
Silvia Tinelli ◽  
Ilan Juran
Keyword(s):  
Artificial Intelligence ◽  
Water Quality ◽  
Monitoring System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Real Life ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Support Vector ◽  
Exposed Population

Abstract This research aims to simulate bio-contamination risk propagation under real-life conditions in the water distribution system (WDS) of Lille University's Scientific City Campus (France), solving the source identification and the response modeling. Neglecting dynamic reactions and not considering the possible chemical decay of most of the contaminants leads to an overestimation of the exposed population. Therefore, unlike the available event detection models, this study considers the interrelated change of several water-quality parameters such as free chlorine concentration, pH, alkalinity, and total organic carbon (TOC) resulting from the pollutants blending. In fact, starting from regular WDS monitoring, the baseline thresholds for each of the mentioned parameters are established; then, significant deviations from the baseline are used as indication for contaminations. For this reason, the purpose of the research was to develop and demonstrate the feasibility of an artificial intelligence (AI)-based smart monitoring system that will effectively enable water operators to ensure a quasi real-time quality control for early chemical and/or bio-contamination detection and preemptive risk management. Advanced pattern recognizers, such as Support Vector Machines (SVMs), and innovative sensing technology solutions, such as Artificial Neural Network (ANN), have been used for this purpose, identifying the anomalies and the severity-level assessment.

scholarly journals Assessment of probable causes of chlorine decay in water distribution systems of Gaborone city, Botswana

Water SA ◽  
2019 ◽  
Vol 45 (2 April) ◽  
Author(s):  
Denis Nono ◽  
Phillimon T Odirile ◽  
Innocent Basupi ◽  
Bhagabat P Parida
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Inorganic Compounds ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Biofilm Growth ◽  
Reaction Rate Constants ◽  
Chlorine Decay

Assessment of probable causes of chlorine decay in water distribution systems of Gaborone city, Botswana Gaborone city water distribution system (GCWDS) is rapidly expanding and has been faced with the major problems of high water losses due to leakage, water shortages due to drought and inadequate chlorine residuals at remote areas of the network. This study investigated the probable causes of chlorine decay, due to pipe wall conditions and distribution system water quality in the GCWDS. An experimental approach, which applied a pipe-loop network model to estimate biofilm growth and chlorine reaction rate constants, was used to analyse pipe wall chlorine decay. Also, effects of key water quality parameters on chlorine decay were analysed. The water quality parameters considered were: natural organic matter (measured by total organic carbon, TOC; dissolved organic carbon, DOC; and ultraviolet absorbance at wavelength 254, UVA-254, as surrogates), inorganic compounds (iron and manganese) and heterotrophic plate count (HPC). Samples were collected from selected locations in the GCWDS for analysis of water quality parameters. The results of biofilm growth and chlorine reaction rate constants revealed that chlorine decay was higher in pipe walls than in the bulk of water in the GCWDS. The analysis of key water quality parameters revealed the presence of TOC, DOC and significant levels of organics (measured by UVA-254), which suggests that organic compounds contributed to chlorine decay in the GCWDS. However, low amounts of iron and manganese (< 0.3 mg/L) indicated that inorganic compounds may have had insignificant contributions to chlorine decay. The knowledge gained on chlorine decay would be useful for improving water treatment and network operating conditions so that appropriate chlorine residuals are maintained to protect the network from the risks of poor water quality that may occur due to the aforementioned problems.

scholarly journals Influence of water quality on nitrifier regrowth in two full-scale drinking water distribution systems

2015 ◽  
Vol 61 (12) ◽  
pp. 965-976 ◽  
Author(s):  
Daniel B. Scott ◽  
Michele I. Van Dyke ◽  
William B. Anderson ◽  
Peter M. Huck
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Quality Parameters ◽  
Full Scale ◽  
Water Quality Parameters ◽  
Drinking Water Distribution Systems ◽  
Drinking Water Distribution

The potential for regrowth of nitrifying microorganisms was monitored in 2 full-scale chloraminated drinking water distribution systems in Ontario, Canada, over a 9-month period. Quantitative PCR was used to measure amoA genes from ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA), and these values were compared with water quality parameters that can influence nitrifier survival and growth, including total chlorine, ammonia, temperature, pH, and organic carbon. Although there were no severe nitrification episodes, AOB and AOA were frequently detected at low concentrations in samples collected from both distribution systems. A culture-based presence–absence test confirmed the presence of viable nitrifiers. AOB were usually present in similar or greater numbers than AOA in both systems. As well, AOB showed higher regrowth potential compared with AOA in both systems. Statistically significant correlations were measured between several water quality parameters of relevance to nitrification. Total chlorine was negatively correlated with both nitrifiers and heterotrophic plate count (HPC) bacteria, and ammonia levels were positively correlated with nitrifiers. Of particular importance was the strong correlation between HPC and AOB, which reinforced the usefulness of HPC as an operational parameter to measure general microbiological conditions in distribution systems.

scholarly journals Assessing the Effect of Changing Ambient Air Temperature on Water Temperature and Quality in Drinking Water Distribution Systems

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1916
Author(s):  
Yuchuan Lai ◽  
David A. Dzombak
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Air Temperature ◽  
Distribution Systems ◽  
Water Distribution ◽  
Ambient Air ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Temperature Changes ◽  
Drinking Water Distribution Systems

Drinking water distribution systems (DWDS) are affected by climate change and this work aimed to assess the effect of changing ambient air temperature on the water temperature and various water quality parameters in DWDS. A water temperature estimation model was identified and evaluated at seven specific locations in the U.S. and water quality parameters were assessed with a case study for Washington D.C. Preliminary estimation of changes in water temperature and two temperature-related parameters (the chlorine decay rate and bacterial activity) were developed for 91 U.S. cities using local air temperature observations and projections. Estimated water temperature changes in DWDS are generally equivalent to air temperature changes on an annual average basis, suggesting modest changes for the assessed historical periods and possibly more intensified changes in the future with greater increase in air temperature. As higher water age can amplify the temperature effect and the effects of temperature on some water quality parameters can be inter-related, yielding an aggregated effect, evaluation of extreme cases for DWDS will be of importance. In responding to changing climate conditions, assessments of DWDS water temperature changes and resulting impacts on water quality merit more attention to ensure appropriate adaptation of DWDS design and management.

scholarly journals Research and Design of Distributed IoT Water Environment Monitoring System Based on LoRa

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wei Chen ◽  
Xiao Hao ◽  
JianRong Lu ◽  
Kui Yan ◽  
Jin Liu ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Real Time ◽  
Monitoring System ◽  
Water Environment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Environment Monitoring ◽  
Long Distance ◽  
Internet Of Things Technology

In order to solve the problems of high labor cost, long detection period, and low degree of information in current water environment monitoring, this paper proposes a lake water environment monitoring system based on LoRa and Internet of Things technology. The system realizes remote collection, data storage, dynamic monitoring, and pollution alarm for the distributed deployment of multisensor node information (water temperature, pH, turbidity, conductivity, and other water quality parameters). Moreover, the system uses STM32L151C8T6 microprocessor and multiple types of water quality sensors to collect water quality parameters in real time, and the data is packaged and sent to the LoRa gateway remotely by LoRa technology. Then, the gateway completes the bridging of LoRa link to IP link and forwards the water quality information to the Alibaba Cloud server. Finally, end users can realize the water quality control of monitored water area by monitoring management platform. The experimental results show that the system has a good performance in terms of real-time data acquisition accuracy, data transmission reliability, and pollution alarm success rate. The average relative errors of water temperature, pH, turbidity, and conductivity are 0.31%, 0.28%, 3.96%, and 0.71%, respectively. In addition, the signal reception strength of the system within 2 km is better than -81 dBm, and the average packet loss rate is only 94%. In short, the system’s high accuracy, high reliability, and long distance characteristics meet the needs of large area water quality monitoring.

scholarly journals ASSESSMENT OF SEAGRASS PERCENT COVER AND WATER QUALITY USING UAV IMAGES AND FIELD MEASUREMENTS IN BOLINAO, PANGASINAN

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 233-240
Author(s):  
M. K. M. R. Guerrero ◽  
J. A. M. Vivar ◽  
R. V. Ramos ◽  
A. M. Tamondong
Keyword(s):  
Water Quality ◽  
Regression Analysis ◽  
Chlorophyll A ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Support Vector ◽  
Percent Cover ◽  
Chl A ◽  
Relationship Of ◽  
The Relationship

Abstract. The sensitivity to changes in water quality inherent to seagrass communities makes them vital for determining the overall health of the coastal ecosystem. Numerous efforts including community-based coastal resource management, conservation and rehabilitation plans are currently undertaken to protect these marine species. In this study, the relationship of water quality parameters, specifically chlorophyll-a (chl-a) and turbidity, with seagrass percent cover is assessed quantitatively. Support Vector Machine, a pixel-based image classification method, is applied to determine seagrass and non-seagrass areas from the orthomosaic which yielded a 91.0369% accuracy. In-situ measurements of chl-a and turbidity are acquired using an infinity-CLW water quality sensor. Geostatistical techniques are utilized in this study to determine accurate surfaces for chl-a and turbidity. In two hundred interpolation tests for both chl-a and turbidity, Simple Kriging (Gaussian-model type and Smooth- neighborhood type) performs best with Mean Prediction equal to −0.1371 FTU and 0.0061 μg/L, Root Mean Square Standardized error equal to −0.0688 FTU and −0.0048 μg/L, RMS error of 8.7699 FTU and 1.8006 μg/L and Average Standard Error equal to 10.8360 FTU and 1.6726 μg/L. Zones are determined using fishnet tool and Moran’s I to calculate for the seagrass percent cover. Ordinary Least Squares (OLS) is used as a regression analysis to quantify the relationship of seagrass percent cover and water quality parameters. The regression analysis result indicates that turbidity has an inverse relationship while chlorophyll-a has a direct relationship with seagrass percent cover.

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