scholarly journals Minimum Night Flow Analysis and Application of the Fixed and Variable Area Discharges Model for Characterizing Leakage in the Gorino Ferrarese (FE-Italy) District

2020 ◽  
Vol 2 (1) ◽  
pp. 8
Author(s):  
Irene Marzola ◽  
Stefano Alvisi ◽  
Marco Franchini
Keyword(s):  
Time Series ◽  
Distribution Systems ◽  
Water Distribution ◽  
Flow Analysis ◽  
Water Utilities ◽  
Smart Meters ◽  
Minimum Night Flow ◽  
Major Interest ◽  
The Relationship ◽  
District Metered Area

Leakage in water distribution systems is an important issue and of major interest for water utilities. In this study, the Minimum Night Flow (MNF) method to quantify the amount of water lost and the equations representing the relationship between pressure and leakage in power and FAVAD (Fixed and Variable Area Discharge) forms were applied to a District Metered Area (DMA) located in Gorino Ferrarese (FE, Italy) equipped with smart meters. The analysis carried out by exploiting the collected time series of user water consumption, DMA inflow, and pressure highlighted that: (a) the MNF method can lead to significant inaccuracy in leakage estimation in the presence of users with irregular consumptions, when based on literature values, and (b) the estimation of the parameters of the power and FAVAD equation is highly affected by the number and types of observed data used.

scholarly journals Analysis of MNF and FAVAD Models for Leakage Characterization by Exploiting Smart-Metered Data: The Case of the Gorino Ferrarese (FE-Italy) District

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 643
Author(s):  
Irene Marzola ◽  
Stefano Alvisi ◽  
Marco Franchini
Keyword(s):  
Time Series ◽  
Water Balance ◽  
Water Consumption ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Utilities ◽  
Time Step ◽  
Minimum Night Flow ◽  
The Relationship ◽  
District Metered Area

Leakages in water distribution systems have great economic and environmental impacts and are a major issue for water utilities. In this work, the water balance and the Minimum Night Flow (MNF) method for evaluating the amount of water loss, as well as the power and Fixed and Variable Area Discharge (FAVAD) equations for analyzing the relationship between leakage and pressure, were applied to a fully monitored District Metered Area (DMA) located in Gorino Ferrarese (FE, Italy). Time series of (a) the water consumption of each user, (b) the DMA inflow, and (c) the pressure at the DMA inlet point were monitored with a 5 min time step. The results of an analysis carried out by exploiting the collected time series highlighted that: (a) The application of the MNF method based on literature values can lead to significant inaccuracies in the presence of users with irregular consumption, and (b) the estimation of the parameters of the power and FAVAD equations is highly affected by the amounts and types of observed data used.

DASH of Water – water distribution system modelling in the age of smart water meters

2020 ◽  
Author(s):  
David Steffelbauer ◽  
Mirjam Blokker ◽  
Arno Knobbe ◽  
Edo Abraham
Keyword(s):  
Drinking Water ◽  
Distribution Systems ◽  
Water Distribution ◽  
Data Science ◽  
Water Systems ◽  
Simulation Software ◽  
Water Utilities ◽  
Smart Meter ◽  
Smart Meters ◽  
Demand Models

<p>Worldwide, water utilities face exceptional challenges as communities are running out of water and new resources are ill-equipped to meet rising water demands. Furthermore, in many cities, years of stringent financial constraints on water utilities, unoptimized operations and the unaffordability for utilities to maintain and replace their aging infrastructure has resulted in dramatically growing leakage levels, especially in places already under high water stress. Even in Europe, as a matter of fact, nearly one quarter of treated water is lost in the distribution systems before reaching the customers. As a result, the aging water infrastructure is challenged to become more efficient.</p><p>Nowadays, an increasing number of water utilities use hydraulic simulation software to design and operate water systems in a more efficient way. However, measurements in water distribution are scarce, which results in inaccurate computer models of real systems. Recently, smart meters have become available as a promising remedy. These smart meters measure water usage of households and transmit information to water utilities in real-time. Now is the time to make water distribution simulation software fit for the future, by exploiting this new Big-data source and start a new era in hydraulic modeling, aiming to increase the operational efficiency of our drinking water systems and save our precious water resources.</p><p>This work proposes an innovative new way of combining hydraulic models, data from smart meters and stochastic demand modelling to develop beyond state-of-the-art methods to simulate water distribution systems. It is shown how data science algorithms (e.g. dynamic time warping, clustering, demand disaggregation, household activity identification, …) can be used to extract high-level information from smart meter data (e.g. daily water use routines, work schedules, socio-economic characteristics). Such information is crucial for simulating water demand accurately. Hence, data science algorithms can be used to automatically parametrize stochastic demand models (e.g. SIMDEUM) based on smart meter data, and improve their accuracy. The improved demand models are coupled with hydraulic simulations, leading to a more realistic way of simulating real water systems. Examples on a wide range of real-world applications show how these novel modelling approaches can be used to increase the operational efficiency of drinking water systems. For instance, more accurate models enable faster detection and localization of leaks in water pipes and, thus, minimize distribution losses. This work is part of the project “DASH of Water”, which aims to develop advanced <strong>da</strong>ta-driven <strong>s</strong>tochastic <strong>h</strong>ydraulic (DASH) models of drinking water distribution systems.</p>

scholarly journals WDSchain: A Toolbox for Enhancing the Security Using Blockchain Technology in Water Distribution System

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1944
Author(s):  
Haitham H. Mahmoud ◽  
Wenyan Wu ◽  
Yonghao Wang
Keyword(s):  
Time Series ◽  
Distribution Systems ◽  
Water Distribution ◽  
Time Series Data ◽  
Series Data ◽  
Process Time ◽  
Time Interval ◽  
Security Level ◽  
Data Validation ◽  
Simulated Time

This work develops a toolbox called WDSchain on MATLAB that can simulate blockchain on water distribution systems (WDS). WDSchain can import data from Excel and EPANET water modelling software. It extends the EPANET to enable simulation blockchain of the hydraulic data at any intended nodes. Using WDSchain will strengthen network automation and the security in WDS. WDSchain can process time-series data with two simulation modes: (1) static blockchain, which takes a snapshot of one-time interval data of all nodes in WDS as input and output into chained blocks at a time, and (2) dynamic blockchain, which takes all simulated time-series data of all the nodes as input and establishes chained blocks at the simulated time. Five consensus mechanisms are developed in WDSchain to provide data at different security levels using PoW, PoT, PoV, PoA, and PoAuth. Five different sizes of WDS are simulated in WDSchain for performance evaluation. The results show that a trade-off is needed between the system complexity and security level for data validation. The WDSchain provides a methodology to further explore the data validation using Blockchain to WDS. The limitations of WDSchain do not consider selection of blockchain nodes and broadcasting delay compared to commercial blockchain platforms.

Kinetic aspects of biofilm formation on surfaces exposed to drinking water

1995 ◽  
Vol 32 (8) ◽  
pp. 61-65 ◽  
Author(s):  
D. van der Kooij ◽  
H. S. Vrouwenvelder ◽  
H. R. Veenendaal
Keyword(s):  
Drinking Water ◽  
Biofilm Formation ◽  
Distribution Systems ◽  
Water Distribution ◽  
Formation Rate ◽  
Water Distribution Systems ◽  
Acetate Concentration ◽  
Drinking Water Distribution Systems ◽  
Drinking Water Distribution ◽  
The Relationship

Biofilm formation in drinking water distribution systems should be limited to prevent the multiplication of undesirable bacteria and other organisms. Certain types of drinking water with an AOC concentration below 10 μg of acetate-C eq/l can support the growth of Aeromonas. Therefore, the effect of acetate at a concentration of 10 μg of C/l on the biofilm formation rate (BFR) of drinking water with a low AOC concentration (3.2 μg C/l) was determined. Drinking water without acetate had a BFR of 3.9 pg ATP/cm2.day, whereas a BFR value of 362 pg ATP/cm2.day was found with acetate added. These data indicate that a low acetate concentration strongly affects biofilm formation, and that only a small fraction of AOC is available for biofilm formation. Aeromonads did not multiply in the biofilm despite their ability to grow at a concentration of 10 μg of acetate-C/l. Further investigations are needed to elucidate the relationship between substrate concentration and biofilm formation in drinking water distribution systems and the growth of undesirable bacteria in these biofilms.

Event Detection in Water Distribution Systems from Multivariate Water Quality Time Series

2012 ◽  
Vol 46 (15) ◽  
pp. 8212-8219 ◽  
Author(s):  
Lina Perelman ◽  
Jonathan Arad ◽  
Mashor Housh ◽  
Avi Ostfeld
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Event Detection ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems

scholarly journals A Pressure Monitoring System for Water Distribution Networks Based on Arduino Microcontroller

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2321
Author(s):  
Federica Bruno ◽  
Mauro De Marchis ◽  
Barbara Milici ◽  
Domenico Saccone ◽  
Fabrizio Traina
Keyword(s):  
Monitoring System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Pressure ◽  
Distribution Networks ◽  
Water Utilities ◽  
Water Distribution Networks ◽  
Prototype System ◽  
Pressure Monitoring ◽  
Arduino Microcontroller

Efficient management of water distribution networks (WDNs) is currently a focal point, especially in countries where water scarcity conditions are more and more amplified by frequent drought periods. In these cases, in fact, pressure becomes the fundamental variable in managing the WDNs. Similarly, WDNs are often obsolete and affected by several points of water losses. Leakages are mainly affected by pressure; in fact, water utilities usually apply the technique of pressure management to reduce physical losses. It is clear how pressure plays a fundamental role in the management of WDNs and in water safety. Even though the technologies are quite mature, these systems are often expensive, especially if a capillarity monitoring system is required; thus, water managers apply the measurement of the flow rate and pressure at very few points. Today, the implementation of the Internet of things (IoT) can be considered a key strategy for monitoring water distribution systems. Once the sensors are installed, in fact, it is relatively easy to build a communication system able to collect and send data from the network. In the proposed study, a smart pressure monitoring system was developed using low-cost hardware and open-source software. The prototype system is composed of an Arduino microcontroller, a printed circuit board, and eight pressure transducers. The efficiency of the proposed tool was compared with a SCADA monitoring system. To investigate on the efficiency of the proposed measurement system, an experimental campaign was carried out at the Environmental Hydraulic Laboratory of the University of Enna (Italy), and hydrostatic as well as hydrodynamic tests were performed. The results showed the ability of the proposed pressure monitor tool to have control of the water pressure in a WDN with a simple, scalable, and economic system. The proposed system can be easily implemented in a real WDN by water utilities, thus improving the knowledge of pressure and increasing the efficiency level of the WDN management.

scholarly journals Microbial Nitrogen Metabolism in Chloraminated Drinking Water Reservoirs

2019 ◽  
Author(s):  
Sarah C Potgieter ◽  
Zihan Dai ◽  
Stefanus N Venter ◽  
Makhosazana Sigudu ◽  
Ameet J Pinto
Keyword(s):  
Nitric Oxide ◽  
Drinking Water ◽  
Nitrogen Metabolism ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Utilities ◽  
Quality Data ◽  
Water Reservoirs ◽  
Microbial Nitrogen ◽  
Drinking Water Distribution

AbstractNitrification is a common concern in chloraminated drinking water distribution systems. The addition of ammonia promotes the growth of nitrifying organisms, causing the depletion of chloramine residuals and resulting in operational problems for many drinking water utilities. Therefore, a comprehensive understanding of the microbially mediated processes behind nitrogen metabolism together with chemical water quality data, may allow water utilities to better address the undesirable effects caused by nitrification. In this study, a metagenomic approach was applied to characterise the microbial nitrogen metabolism within chloraminated drinking water reservoirs. Samples from two geographically separated but connected chloraminated reservoirs within the same drinking water distribution system (DWDS) were collected within a 2-year sampling campaign. Spatial changes in the nitrogen compounds (ammonium (NH4+), nitrites (NO2−) and nitrates (NO3−)) across the DWDS were observed, where nitrate concentrations increased as the distance from the site of chloramination increased. The observed dominance ofNitrosomonasandNitrospira-like bacteria, together with the changes in the concentration of nitrogen species, suggests that these bacteria play a significant role in contributing to varying stages of nitrification in both reservoirs. Functionally annotated protein sequences were mined for the genes associated with nitrogen metabolism and the community gene catalogue contained mostly genes involved in nitrification, nitrate and nitrite reduction and nitric oxide reduction. Furthermore, based on the construction of Metagenome Assembled Genomes (MAGs), a highly diverse assemblage of bacteria (i.e., predominatelyAlpha- andBetaproteobacteriain this study) was observed among the draft genomes. Specifically, 5 MAGs showed high coverage across all samples including twoNitrosomonas, Nitrospira, Sphingomonasand aRhizobiales-like MAGs. The role of these MAGs in nitrogen metabolism revealed that the fate nitrate may be linked to changes in ammonia concentrations, that is, when ammonia concentrations are low, nitrate may be assimilated back to ammonia for growth. Alternatively, nitrate may be reduced to nitric oxide and potentially used in the regulation of biofilm formation. Therefore, this study provides insight into the genetic network behind microbially mediated nitrogen metabolism and together with the water chemistry data improves our understanding nitrification in chloraminated DWDSs.

scholarly journals Water leakage detection and localization using hydraulic modeling and classification

2021 ◽  
Author(s):  
Eliyas Girma Mohammed ◽  
Ethiopia Bisrat Zeleke ◽  
Surafel Lemma Abebe
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Hybrid Approach ◽  
Leak Detection ◽  
Hydraulic Modeling ◽  
Hydraulic Model ◽  
Leakage Detection ◽  
Minimum Night Flow ◽  
Two Phases ◽  
Detection And Localization

Abstract A significant percentage of treated water is lost due to leakage in water distribution systems. The state-of-the-art leak detection and localization schemes use a hybrid approach of hydraulic modeling and data-driven techniques. Most of these works, however, focus on single leakage detection and localization. In this research, we propose to use combined pressure and flow residual data to detect and localize multiple leaks. The proposed approach has two phases: detection and localization. The detection phase uses the combination of pressure and flow residuals to build a hydraulic model and classification algorithm to identify leaks. The localization phase analyzes the pattern of isolated leak residuals to localize multiple leaks. To evaluate the performance of the proposed approach, we conducted experiments using Hanoi Water Network benchmark and a dataset produced based on LeakDB benchmark's dataset preparation procedure. The result for a well-calibrated hydraulic model shows that leak detection is 100% accurate while localization is 90% accurate, thereby outperforming minimum night flow and raw- and residual-based methods in localizing leaks. The proposed approach performed relatively well with the introduction of demand and noise uncertainty. The proposed localization approach is also able to locate two to four leaks that existed simultaneously.

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