Conductance-based interface detection for multi-phase pipe flow

Sediment and flow depth monitoring in sewers is important for informing flow models and for predicting and mitigating against sewer blockage formation and surcharge. In this study, a novel sensor based on conductance measurement has been developed and tested under a laboratory environment and validated by a finite-element model. The relative conductance is measured between pairs of adjacent electrodes to provide a conductance profile along the sensor length. A piecewise linear relationship between conductance and electrode length was derived and the interface positions between sediment, water, and air can be determined from the profile. The results demonstrated that the root mean square error of the model and the measured interface level are within 1.4% and 2.6% of sensor’s measurement range. An error distribution of interface height shows that all anticipated errors are within the resolution of the electrode length increments. Furthermore, it was found that the conductivity of the measured medium is proportional to the gradient of the linear relationship of conductance and electrode length. It could therefore prove a valuable new tool for the accurate quantification of sediment and flow levels in sewer conduits, coastal environments, drainage systems for transport networks, and other industrial or academic applications

Understanding Combined Sewer Overflow (CSO) and Green Infrastructure Interaction in New Jersey : An Economic Analysis

New Jersey, as a coastal area, has historically struggled with a variety of problems stemming from stormwater runoff, which have only grown more prevalent and harmful as urbanization and climate change have taken their toll. One such issue that has emerged in recent years is the prevalence of combined sewer overflows (CSOs). These sewer systems are common in urban areas in the United States and abroad, and increased urbanization has them not only obsolete but a persistent danger, as their discharges can contaminate waterways and affect human health. While municipalities across the United States are beginning to move towards mitigating or replacing CSO systems, many areas still struggle to do so due to cost. Further, few studies have been done to understand the full cost of CSOs, as externalities such as effects on society or housing markets are largely understudied. As such, this study proposes a number of interlinked economic valuations to understand the costs of CSOs and the benefits of their solutions. To understand costs, we utilize a hedonic analysis using observable real estate data to understand the economic impact of CSOs on the housing market. As CSOs are heavily regulated by the EPA, there is significant value in also understanding the benefit of possible solutions to the problems that CSOs represent. To this end, we analyze green infrastructure, which has been used extensively around the United States and abroad to cheaply and effectively limit CSO discharges. We use a choice-experiment survey to delineate willingness to pay in target cities, and to understand preferences of residents in terms of green infrastructure capabilities and payment vectors for funding such projects. Finally, we use an ArcGIS linked framework to analyze the potential benefit of green infrastructure in terms of runoff reductions, and understand what land use types are ideal for installation. The combination of these economic analyses should give a more complete picture of the full cost of these fixtures than has existed in the literature to date, and can be useful to researchers and decision makers alike

Digitalization and real-time control to mitigate environmental impacts along rivers: Focus on artificial barriers, hydropower systems and European priorities

Hydropower globally represents the main source of renewable energy, and provides several benefits, e.g., water storage and flexibility; on the other hand, it may cause significant impacts on the environment. Hence sustainable hydropower needs to achieve a balance between electricity generation, impacts on ecosystems and benefits on society, supporting the achievement of the Green Deal targets. The implementation of digital, information, communication and control (DICC) technologies is emerging as an effective strategy to support such a trade-off, especially in the European Union (EU), fostering both the green and the digital transitions. In this study, we show how DICC can foster the environmental integration of hydropower into the Earth spheres, with focus on the hydrosphere (e.g., on water quality and quantity, hydropeaking mitigation, environmental flow control), biosphere (e.g., improvement of riparian vegetation, fish habitat and migration), atmosphere (reduction of methane emissions and evaporation from reservoirs), lithosphere (better sediment management, reduction of seepages), and on the anthroposphere (e.g., reduction of pollution associated to combined sewer overflows, chemicals, plastics and microplastics). With reference to the abovementioned Earth spheres, the main DICC applications, case studies, challenges, Technology Readiness Level (TRL), benefits and limitations, and transversal benefits for energy generation and predictive Operation and Maintenance (O&M), are discussed. The priorities for the European Union are highlighted. Although the paper focuses primarly on hydropower, analogous considerations are valid for any artificial barrier, water reservoir and civil structure which interferes with freshwater systems.Digitalization and real-time control to mitigate environmental impacts along rivers: Focus on artificial barriers, hydropower systems and European prioritiespublishedVersio

Data Analytics for Automated Near Real Time Detection of Blockages in Smart Wastewater Systems

Blockage events account for a substantial portion of the reported failures in the wastewater network, causing flooding, loss of service, environmental pollution and significant clean-up costs. Increasing telemetry in Combined Sewer Overflows (CSOs) provides the opportunity for near real-time data-driven modelling of the sewer network. The research work presented in this thesis describes the development and testing of a novel system, designed for the automatic detection of blockages and other unusual events in near real-time. The methodology utilises an Evolutionary Artificial Neural Network (EANN) model for short term CSO level predictions and Statistical Process Control (SPC) techniques to analyse unusual CSO level behaviour. The system is designed to mimic the work of a trained, experience human technician in determining if a blockage event has occurred. The detection system has been applied to real blockage events from a UK wastewater network. The results obtained illustrate that the methodology can identify different types of blockage events in a reliable and timely manner, and with a low number of false alarms. In addition, a model has been developed for the prediction of water levels in a CSO chamber and the generation of alerts for upcoming spill events. The model consists of a bi-model committee evolutionary artificial neural network (CEANN), composed of two EANN models optimised for wet and dry weather, respectively. The models are combined using a non-linear weighted averaging approach to overcome bias arising from imbalanced data. Both methodologies are designed to be generic and self-learning, thus they can be applied to any CSO location, without requiring input from a human operator. It is envisioned that the technology will allow utilities to respond proactively to developing blockages events, thus reducing potential harm to the sewer network and the surrounding environment

The Identification and Quantification of Sewage Contamination in the Milwaukee Estuary

Sewage contamination from failing infrastructure and sewer overflows is a major environmental and human health concern in waterways, especially in urban communities bordering the Great Lakes such as Milwaukee, Wisconsin. Culture-based fecal indicator bacteria, such as Escherichia coli, enterococci, and fecal coliforms are traditionally used to indicate the presence of a human health risk due to fecal contamination. These indicators, however, fail to distinguish between sources of fecal contamination (human vs. non-human). Two human-specific fecal indicators, human Bacteroides and human Lachnospiraceae, were used to identify and quantify sewage contamination in the Milwaukee estuary, which discharges to Lake Michigan, as well as the Milwaukee, Menomonee, and Kinnickinnic Rivers immediately upstream. Chapter 1 provides an overview of the health and environmental impacts of fecal pollution in waterways and the use of alternative indicators to track sewage pollution. Chapter 2 describes the concentrations of human fecal indicators, used as a proxy for human sewage, in the three urban rivers upstream of the Milwaukee estuary and how this information can be used for the implementation stage of the current fecal coliforms Total Maximum Daily Load (TMDL) process. Chapter 3 describes how human fecal indicators were used to characterize sewage contamination across the hydrograph. Intensive monitoring at sites in the rivers and the estuary was used to calculate event loads for storm and combined sewer overflow events and investigate relationships between loads and the degree of watershed urbanization and the amount of rainfall during an event. Chapter 4 discusses how the information generated in this research can be used in the TMDL implementation process and can be used to focus efforts of local agencies and municipalities to investigate and remediate unrecognized sources of sewage contamination. More specific information about sources of fecal pollution will be useful to create appropriate water quality goals to address the human health concerns of sewage contamination

Optimal sensor placement for sewer capacity risk management

2019 Spring.Includes bibliographical references.Complex linear assets, such as those found in transportation and utilities, are vital to economies, and in some cases, to public health. Wastewater collection systems in the United States are vital to both. Yet effective approaches to remediating failures in these systems remains an unresolved shortfall for system operators. This shortfall is evident in the estimated 850 billion gallons of untreated sewage that escapes combined sewer pipes each year (US EPA 2004a) and the estimated 40,000 sanitary sewer overflows and 400,000 backups of untreated sewage into basements (US EPA 2001). Failures in wastewater collection systems can be prevented if they can be detected in time to apply intervention strategies such as pipe maintenance, repair, or rehabilitation. This is the essence of a risk management process. The International Council on Systems Engineering recommends that risks be prioritized as a function of severity and occurrence and that criteria be established for acceptable and unacceptable risks (INCOSE 2007). A significant impediment to applying generally accepted risk models to wastewater collection systems is the difficulty of quantifying risk likelihoods. These difficulties stem from the size and complexity of the systems, the lack of data and statistics characterizing the distribution of risk, the high cost of evaluating even a small number of components, and the lack of methods to quantify risk. This research investigates new methods to assess risk likelihood of failure through a novel approach to placement of sensors in wastewater collection systems. The hypothesis is that iterative movement of water level sensors, directed by a specialized metaheuristic search technique, can improve the efficiency of discovering locations of unacceptable risk. An agent-based simulation is constructed to validate the performance of this technique along with testing its sensitivity to varying environments. The results demonstrated that a multi-phase search strategy, with a varying number of sensors deployed in each phase, could efficiently discover locations of unacceptable risk that could be managed via a perpetual monitoring, analysis, and remediation process. A number of promising well-defined future research opportunities also emerged from the performance of this research

An Integrative Investigation of Sources, Fate, and Transport of Bacteria in Milwaukee Coastal Beaches

Beach water quality criteria are determined by the Environmental Protection Agency (EPA) and water quality advisories or closings are issued based on fecal indicator bacteria (FIB) at the beaches. Understanding of sources, fate and transport of FIB at a beach environment is of economic and social interest for public users, beach managers, policy makers and scientists. This is a complex problem and it is a multidisciplinary issue by nature. Scientists have generally taken a reductionist approach to tackle complex environmental issues. However, as alluded by Gallagher and Appenzeller (1999) and adopted by Boehm (2000), many complex systems are best interpreted using an integrative agenda . Sources and transport of bacteria at a beach environment has been studied by Boehm (2012) in this context. Results from such study indicate that large scale feature is best interpreted with information about small-scale interactions. In this dissertation, I examined the sources of fecal indicator bacteria (FIB) in ten Lake Michigan beaches. In depth studies were performed at one study site (Bradford Beach) to investigate possible sources of FIB, including groundwater-lake water interactions and runoff infiltrating through the sand. The impact of hydrological and geophysical factors that are associated with formation of standing water were also investigated, including the potential of FIB reservoirs in the sand matrix to serve as a sink and source of bacteria at the beach environment. In order to better understand bacterial association with particles at a large scale, I examined the small scale interactions between bacteria and particles by developing a new non-invasive optical technique and applying the technique to assess attachment of bacteria to sand particles in a sheared fluid simulating condition found in the surf zone. Finally, I used knowledge obtained from the understanding of small scale interactions to interpret results acquired from a statistical model and time series applied to large scale features at Bradford Beach and Atwater Beach. This work is relevant to the study of sources and transport of bacteria not only in large lakes, but in rivers and oceans. The results also extend to the investigation of other microbial pollutants and their association with particles in a water body and the potential to track the transport of these pollutants in sediments, air and water. References: Boehm, A. (2000). An integrative investigation of particle distributions in natural waters. Department of Chemical and Biochemical Engineering and Materials Science. Irvine, University of California, Irvine: 194. Gallagher, R and T. Appenzeller (1999). Beyond reductionism. Science 284:79. Russell, T. L., K. M. Yamahara and A. B. Boehm (2012). Mobilization and transport of naturally occurring enterococci in beach sands subject to transient infiltration of seawater. Environmental Science and Technology 46:5988-5996

Hydrolink 2021/2. Artificial Intelligence

Topic: Artificial Intelligenc

The Impact of Event-Based Cryptosporidium and Giardia Loads on Drinking Water Risk

RÉSUMÉ: Des épidémies de maladies d'origine hydrique ont été documentées dans le monde entier. Deux épidémies majeures d'origine hydrique se sont produites à Milwaukee, dans le Wisconsin et à Walkerton, en Ontario, au cours des trois dernières décennies, entraînant des modifications de la réglementation en matière de protection des sources d’approvisionnement en eau potable. Les épidémies signalées se sont principalement produites à la suite d'épisodes de fortes précipitations, indiquant un lien étroit entre l'hydrologie des bassins versants et les épidémies d'origine hydrique. L'approche multi-barrières, de la source au robinet, est recommandée en tant qu'approche préventive afin de protéger la santé publique et de fournir une eau potable propre et fiable aux consommateurs.----------ABSTRACT: Waterborne disease outbreaks have been documented worldwide. Two major waterborne outbreaks occurred in Milwaukee, Wisconsin and in Walkerton, Ontario over the past three decades leading to regulatory changes for source water protection and drinking water treatment. Reported outbreaks have mostly occurred following heavy rainfall events, indicating a close link between watershed hydrology and waterborne outbreaks. The multi-barrier, source to tap approach is recommended as preventive approach to protect public health and to provide clean, safe and reliable drinking water to water consumers