Rev. ed. of: Modeling water quality in drinking water distribution systems / Robert M. Clark, Walter M. Grayman. 1998.

Accompanying CD-ROM includes: a 25-pipe academic version of WaterCAD with stand-alone interface; the WaterCAD files for individual problems; the WaterCAD user manual and an examination booklet for continuing education credits; Adobe Acrobat Reader software for viewing the manual and booklet.

Protecting and maintaining water distributions systems is crucial to ensuring high quality drinking water. Distribution systems-consisting of pipes, pumps, valves, storage tanks, reservoirs, meters, fittings, and other hydraulic appurtenances-carry drinking water from a centralized treatment plant or well supplies to consumers' taps. Spanning almost 1 million miles in the United States, distribution systems represent the vast majority of physical infrastructure for water supplies, and thus constitute the primary management challenge from both an operational and public health standpoint. Recent data on waterborne disease outbreaks suggest that distribution systems remain a source of contamination that has yet to be fully addressed. This report evaluates approaches for risk characterization and recent data, and it identifies a variety of strategies that could be considered to reduce the risks posed by water-quality deteriorating events in distribution systems. Particular attention is given to backflow events via cross connections, the potential for contamination of the distribution system during construction and repair activities, maintenance of storage facilities, and the role of premise plumbing in public health risk. The report also identifies advances in detection, monitoring and modeling, analytical methods, and research and development opportunities that will enable the water supply industry to further reduce risks associated with drinking water distribution systems.

Analysis of a Water Distribution Network may be necessary to know its behaviour under normal and deficient conditions and the design of a new network. Various methods such as Hardy Cross, Newton-Raphson, Linear Theory, and Gradient for static and time-dependent (extended period) analyses are described with small illustrative examples. The book also covers analysis considering withdrawal along links, head-dependent and performance-based analyses, calibration of existing networks, water quality modeling, analysis considering uncertainty of parameters, and reliability analysis of water distribution networks. Brief description of available computer softwares is also given.

Water Engineering Modeling and Mathematic Tools provides an informative resource for practitioners who want to learn more about different techniques and models in water engineering and their practical applications and case studies. The book provides modelling theories in an easy-to-read format verified with on-site models for specific regions and scenarios. Users will find this to be a significant contribution to the development of mathematical tools, experimental techniques, and data-driven models that support modern-day water engineering applications. Civil engineers, industrialists, and water management experts should be familiar with advanced techniques that can be used to improve existing systems in water engineering. This book provides key ideas on recently developed machine learning methods and AI modelling. It will serve as a common platform for practitioners who need to become familiar with the latest developments of computational techniques in water engineering. - Includes firsthand experience about artificial intelligence models, utilizing case studies - Describes biological, physical and chemical techniques for the treatment of surface water, groundwater, sea water and rain/snow - Presents the application of new instruments in water engineering

There are two groups of specialists involved in the development and application of water quality models, each of which have a different perspective on the use of models: Academics and scientists - chemistry specialists and microbiologists who develop the models. Practitioners - modelers and distribution engineers who use them to solve problems. There are limitations and constraints in the characterization of the underlying processes and the practical application of models to distribution networks, which require further research. The objectives of the research were to characterize the current state of predictive distribution system water quality models and to identify critical research needs for their improvement. The project reviewed both the development and application of models. The report is intended to both steer future research and to act as a general reference on water quality modeling. The report combines a literature review with the practical experience of the project team. The content of a draft report was discussed at an international workshop attended by academics, engineers, scientists, and hydraulic modelers with the objective of agreeing on specific research needs necessary to improve predictive modeling for water quality in distribution systems. The conclusions of the report are derived from the workshop and form the basis of 11 specific research briefs that have been submitted to AwwaRF for consideration of funding. Researchers often focus on modeling the individual processes that control water quality rather than fully modeling water quality throughout distribution systems. For these "process models" to be applied to real distribution networks, they need to be extended to take in account the physical characteristics of the system?the special and temporal variations in flow, velocity and water age, and the effects of mixing water that has traveled along different flow paths.

Prepared by the Water Supply Engineering Technical Committee of the Infrastructure Council of the Environmental and Water Resources Institute of ASCE. This report examines the application of artificial neural network (ANN) technology to water supply engineering problems. Although ANN has rarely been used in in this area, those who have done so report findings that were beyond the capability of traditional statistical and mathematical modeling tools. This report describes the availability of diverse applications, along with the basics of neural network modeling, and summarizes the experiences of groups of researchers around the world who successfully demonstrated significant benefits from using ANN technology in water supply engineering. Topics include: Forecasting salinity levels in River Murray, South Australia; Predicting gastroenteritis rates and waterborne outbreaks; Modeling pH levels in a eutrophic Middle Loire River, France; and ANNs as function approximation tools replacing rigorous mathematical simulation models for analyzing water distribution networks.

Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems.

This book presents the basic principles for evaluating water quality and treatment plant performance in a clear, innovative and didactic way, using a combined approach that involves the interpretation of monitoring data associated with (i) the basic processes that take place in water bodies and in water and wastewater treatment plants and (ii) data management and statistical calculations to allow a deep interpretation of the data. This book is problem-oriented and works from practice to theory, covering most of the information you will need, such as (a) obtaining flow data and working with the concept of loading, (b) organizing sampling programmes and measurements, (c) connecting laboratory analysis to data management, (e) using numerical and graphical methods for describing monitoring data (descriptive statistics), (f) understanding and reporting removal efficiencies, (g) recognizing symmetry and asymmetry in monitoring data (normal and log-normal distributions), (h) evaluating compliance with targets and regulatory standards for effluents and water bodies, (i) making comparisons with the monitoring data (tests of hypothesis), (j) understanding the relationship between monitoring variables (correlation and regression analysis), (k) making water and mass balances, (l) understanding the different loading rates applied to treatment units, (m) learning the principles of reaction kinetics and reactor hydraulics and (n) performing calibration and verification of models. The major concepts are illustrated by 92 fully worked-out examples, which are supported by 75 freely-downloadable Excel spreadsheets. Each chapter concludes with a checklist for your report. If you are a student, researcher or practitioner planning to use or already using treatment plant and water quality monitoring data, then this book is for you! 75 Excel spreadsheets are available to download.