Water Resources planning and management

The paper presents the results of the Battle of Post-Disaster Response and Restoration (BPDRR), presented in a special session at the 1 st International WDSA/CCWI Joint Conference, held in Kingston, Ontario, in July 2018. The BPDRR problem focused on how to respond and restore water service after the occurrence of five earthquake scenarios that cause structural damage in a water distribution system. Participants were required to propose a prioritization schedule to fix the damages of each scenario while following restrictions on visibility/non visibility of damages. Each team/approach was evaluated against six performance criteria that included: 1) Time without supply for hospital/firefighting, 2) Rapidity of recovery, 3) Resilience loss, 4) Average time of no user service, 5) Number of users without service for 8 consecutive hours, and 6) Water loss. Three main types of approaches were identified from the submissions: 1) General purpose metaheuristic algorithms, 2) Greedy algorithms, and 3) Ranking-based prioritizations. All three approaches showed potential to solve the challenge efficiently. The results of the participants showed that, for this network, the impact of a largediameter pipe failure on the network is more significant than several smaller pipes failures. The location of isolation valves and the size of hydraulic segments influenced the resilience of the system during emergencies. On average, the interruptions to water supply (hospitals and firefighting) varied considerably between solutions and emergency scenarios, highlighting the importance of private water storage for emergencies. The effects of damages and repair work were more noticeable during the peak demand periods (morning and noontime) than during the low-flow periods; and tank storage helped to preserve functionality of the network in the first few hours after a simulated event.

Issues around water-its quality, use, availability and environmental value-can be a major point of tension between mineral projects and local communities. Failure to manage these issues appropriately can jeopardise the obtaining of regulatory approvals for new projects and place at risk the 'social licence to operate' of existing operations. Conversely, there may also be significant opportunities for companies to engage constructively with communities over water issues and to make a positive contribution to the sustainable development of these communities. Using case studies, this paper will explore the various types of social risks and opportunities associated with water and mineral resource development and identify key learnings relating to the management of these issues.

Outlines the delta's history and current political context, documents recent findings about the delta's partial recovery, and makes recommendations for maintaining existing flows to further benefit and sustain the remnant wetland ecosystems

Sampling of drinking water distribution systems is performed to ensure good water quality and protect public health. Sampling also satisfies regulatory requirements and is done to respond to customer complaints or emergency situations. Water distribution system modeling techniques can be used to plan and inform sampling strategies. However, a high degree of accuracy and confidence in the hydraulic and water quality models is required to support real-time response. One source of error in these models is related to uncertainty in model input parameters. Effective characterization of these uncertainties and their effect on contaminant transport during a contamination incident is critical for providing confidence estimates in model-based design and evaluation of different sampling strategies. In this paper, the effects of uncertainty in customer demand, isolation valve status, bulk reaction rate coefficient, contaminant injection location, start time, duration and rate on the size and location of the contaminant plume are quantified for two example water distribution systems. Results show that the most important parameter was the injection location. The size of the plume was also affected by the reaction rate coefficient, injection rate and the injection duration, while the the exact location of the plume was additionally affected by the isolation valve status. Uncertainty quantification provides a more complete picture of how contaminants move within a water distribution system and provides more information when using modeling results to select sampling locations.

The Rohingya refugee camps in Bangladesh face severe water resource challenges, exacerbated by the impacts of climate change. With a rapidly growing population, the demand for water in these camps has surged, leading to over-extraction of groundwater and deteriorating water quality. Seasonal variations, including monsoons and dry spells, further strain the limited water resources, creating periods of acute scarcity and contamination risks. Climate change intensifies these issues by altering precipitation patterns and increasing the frequency of extreme weather events, jeopardizing the sustainability of current water supply systems. This paper explores sustainable water resource planning strategies tailored to the unique context of the Rohingya camps, emphasizing climate resilience and community-based approaches. By integrating innovative technologies and policy interventions, the study aims to propose solutions that ensure long-term water security for the refugee population.
Sustainable water resource planning is crucial for addressing the compounded challenges of water scarcity and quality in Rohingya refugee camps, particularly under the escalating pressures of climate change. As climate change alters precipitation patterns and increases the frequency of extreme weather events, the vulnerability of water systems in these densely populated settlements intensifies. Effective planning must integrate climate resilience, ensuring reliable access to safe water despite environmental uncertainties. This involves adopting adaptive management strategies, leveraging innovative technologies, and fostering community participation to enhance system robustness and flexibility. Sustainable planning not only addresses immediate water needs but also builds long-term resilience, reducing dependency on overstressed groundwater resources and mitigating the impacts of climate-induced disruptions. This paper underscores the importance of holistic and forward-thinking approaches in securing water resources for the Rohingya population in the face of a changing climate.
The study identifies critical gaps in current water resource management practices within Rohingya refugee camps and emphasizes the necessity for sustainable planning amidst climate change impacts. Key findings reveal that over-reliance on groundwater, coupled with inadequate infrastructure and seasonal variability, significantly undermines water security. The research recommends the implementation of integrated water resource management (IWRM) strategies, incorporating both traditional and innovative solutions such as rainwater harvesting, solar-powered water purification, and community-led water conservation practices. Enhancing policy frameworks to support sustainable water management and fostering collaborations among stakeholders are also crucial. Furthermore, climate resilience measures, including infrastructure fortification against extreme weather events, are imperative for long-term sustainability. These recommendations aim to establish a resilient water supply system that can adapt to future climate conditions while ensuring equitable access to safe water for the Rohingya population.

This paper examines the effectiveness of hygiene promotion interventions in protecting public health within
the Rohingya refugee settlements in Bangladesh. The study focuses on various strategies implemented to
improve hygiene practices and reduce the inci dence of waterborne diseases among the refugee population. Key
interventions include the distribution of hygiene kits, handwashing campaigns, construction and maintenance
of sanitation facilities, and educational programs tailored to the cultural context o f the Rohingya community.
Through a mixed methods approach in volving quantitative surveys, qualitative interviews, and observational
data, the study assesses changes in hygiene behaviors, knowledge, attitudes, and practices (KAP), as well as
health outcomes. The findings indicate significant improvements in hygiene practice s, such as increased
handwashing with soap, greater use of latrines, and better water storage practices, alongside a notable
reduction in diarrheal disease incidence. The paper also highlights the critical role of community engagement,
cultural sensitivity , and continuous monitoring in enhancing the effectiveness and sustainability of hygiene
interventions. These insights contribute to the broader understanding of public health strategies in
humanitarian settings and provide valuable recommendations for fut ure hygiene promotion efforts in similar
contexts.
This paper
also evaluates the impact of hygiene promotion interventions on public health within the Rohingya
refugee settlements in Bangladesh. Through a mixed methods approach, the study investigates the
effectiveness of various strategies, including the distribution of hygiene kits, handwashing campaigns,
construction of sanitation facilities, and culturally tailored educational programs. The key findings reveal
significant improvements in hygiene practic es, such as increased handwashing with soap from 40% to 75%,
greater use of latrines from 55% to 85%, and enhanced safe water storage practices from 50% to 80% (all p <
0.001). Additionally, the incidence of diarrheal diseases decreased from 35% to 15% (p < 0.001). The study
also highlights an improvement in the knowledge, attitudes, and practices (KAP) scores from 60% to 85% (p <
0.001). Community engagement and culturally sensitive approaches were identified as critical factors
contributing to the success of these interventions. Continuous monitoring and adaptive strategies were essential
for sustaining the positive outcomes. The findings underscore the importance of comprehensive, community
driven, and culturally tailored hygiene promotion interventions i n improving public health outcomes in refugee
settings

Understanding elements of non-revenue water (NRW) has become more critical in an era where urban water has a rapidly increasing value. Meter under-and over-registration of flows has received considerable research attention over the years, but there has been limited focus on non-registration, particularly for domestic water meters over their life cycle. This paper presents empirical estimates on nonregistration for typically installed domestic water meters and emphasises that both under-and non-registration should be considered for any meter replacement assessments and associated policies. Economic modelling showed that domestic water meters should be replaced at lower throughput volumes when considering both of these meter inaccuracy categories. The key value of the paper is that it provides a methodology for determining nonregistration for a fleet of domestic meters.

Essentially, there are two overarching demand management strategies employed to achieve efficient water consumption in the residential sector. These are: targeting water use behaviour change ("mind") and promoting the use of water-efficient technologies ("machine"). Using detailed water end-use data and qualitative methods, this paper describes the role that each of these strategies has played over the last few years, using data from 250 residential properties located in the south-east corner of Queensland. The role of water-efficient technology (e.g. low-flow shower heads, 4-star-rated clothes-washers) in reducing potable demand will be compared with the importance of attitudes and behaviours to water conservation. Results indicate that how we value water (psycho-social variables) and interact with water-efficient fixtures is at least as important in reducing water consumption in the home as the quality and quantity of water-efficient stock. The paper concludes with some suggestions on how such study outcomes can be relevant to future demand management approaches.

Understanding elements of non-revenue water (NRW) has become more critical in an era where urban water has a rapidly increasing value. Meter under-and over-registration of flows has received considerable research attention over the years, but there has been limited focus on non-registration, particularly for domestic water meters over their life cycle. This paper presents empirical estimates on nonregistration for typically installed domestic water meters and emphasises that both under-and non-registration should be considered for any meter replacement assessments and associated policies. Economic modelling showed that domestic water meters should be replaced at lower throughput volumes when considering both of these meter inaccuracy categories. The key value of the paper is that it provides a methodology for determining nonregistration for a fleet of domestic meters.

The COVID-19 pandemic forced many countries to put forth severe lockdown restrictions in order to stop the spread of the virus. Spain was one the most affected countries in Europe, and its non-essential socio-economic activities faced strict restrictions in the free movement of people. Within the Spanish territories the island of Menorca was more vulnerable to these movement restrictions, since it is mostly dependent on external resources and tourism in order to perform its socio-economic activities. Island territories like Menorca are already vulnerable to climate change threats such as sea-level rise and extreme weather patterns, but other non-climate stressors such as pandemics also threaten to render island territories under partial or total isolation. Learning how Menorca’s socio-economic activities operate resource-wise during these periods of isolation can help the island’s government to make decisions to improve their resource security and sustainability of the island. This work studies how the societal metabolism – i.e., the use of resources through the different levels and structures that conform the social system of the island – was like in Menorca under the lockdown restrictions during 2020 using the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach for metabolic analysis; and assesses Menorca’s potential for self-sufficiency. The results of the metabolic analysis show that during 2020 Menorca had a lower energy and water demand as consequence of a great loss of activity in the economic sectors, in particular that of tourism. Lesser energy consumption has translated to lower carbon emissions, and the loss of activity of the economic sectors has meant that the total gross value added generated by the island has also been lower than what the island generates under regular circumstances. This metabolic analysis show how Menorca works under conditions of isolation, reorganizing it hours of activity and use of resources mainly from the touristic sector and giving more emphasis on internal agricultural production. Should Menorca in the future become partly or totally isolated due to other circumstances, an organized rearrangement of its metabolism away from a high dependency on tourism and imports and towards internal production would aid the island to be more self-sufficient.

In this paper the transient behavior of a single-branch pipe system (Y-system) is analyzed by means of numerical experiments in which a wide range of branch characteristics (i.e., size, location, and operating conditions) is investigated. In the executed systematic analysis, focused on the role of minor branches, the pressure signals of the Y-system have been compared with the ones of the single pipe, assumed as a reference, by means of the values of the determination coefficient, 2. The provided explicit relationships between 2 and the characteristics of the branch clearly show that the actual role of the branch is determined by the combination of the characteristics more than by any single one. Such relationships are a reliable tool for the system skeletonization, i.e. they allow evaluating in which conditions a given branch can be neglected since it does not affect

Optimization of short-term reservoir operation normally involves ramping constraints of outflows and water elevations at short time steps (e.g., hourly). Random search algorithms, such as Genetic Algorithms, have been widely used in optimization of reservoir operation. When applying random search algorithms to hourly reservoir operation, two important issues arise. The first one is the frequent violation of ramping constraints on the hourly reservoir outflows due to the random nature of the optimization algorithm. In other words, the optimization struggles to meet the ramping constraints when finding feasible solutions. The second issue is the zigzag fluctuation of the hourly decision variables as a result of the random search, which is unrealistic to implement in practice. In this study, the Savitzky-Golay smoothing filter (also known as least-squares filter) is incorporated periodically within the routine of the Non-dominated Sorting Genetic Algorithm (NSGA-II). The goal of this study is to smooth out the decision variables functions without deteriorating the performance of the optimization algorithm. The performance of the proposed approach is quantified through three indexes using a multi-reservoir system with 3360 decision variables as the test case. The results show that the use of the Savitzky-Golay filter not only

Pressure standards assist in the design of water distribution systems and the assessment of their performance. Although exact thresholds are sometimes rather vague, unusually high and low pressures are widely understood to increase costs and put systems at risk from events like pipe bursts at the high-pressure end to the risk of contaminant intrusion or poor firefighting conditions at the low-pressure end. Interestingly, because the definition of what conditions constitute acceptable pressures differs around the world, a delivery pressure might be considered acceptable in some regions and unacceptable in others. But if a wider range of system conditions is considered, including transient events, an interesting question arises as to what exactly the standards might mean and how violations should be evaluated. Specifically, what kinds of pressure transgressions are most crucial to system performance and economics and what kinds are merely inconvenient? Certainly the issue of evaluating consequences is relevant, but it is also complex because some consequences are not easily attributed to specific system conditions. As this paper considers, the frequency, duration, and intensity of the pressure violation are all relevant, but so is the vulnerability of the system to those violations. Few of these issues have yet received adequate attention, but it is to raising such a discussion that this paper is aimed. There is no doubt that pressure standards can help to assess system performance and to trigger system evolution (i.e., operational and capital investments). But if the criteria themselves, and the means to evaluate them, are too vague, so will be the corrective outcomes.

Increasing and changing product requirements demand a permanent readiness for efficient factory adaption. Considering necessary construction adaptions as well as conventional construction planning processes in the context of the factory adaptation process, standard planning methods are unable to support in a fast and efficient way. By application of the BIM method a Building Information Model, which contains all the needed information in one database is generated. BIM is a method for achieving targets, such as selecting the right type of construction technology or building material to evaluate the adaptation measure. The challenges by putting all information in one model are dealing with the amounts of data, identifying data quality and determining the current use case which should be examined. In this publication, the necessary data base is identified and implemented into a Building Information Model to investigate the right fastening system for an Industry 4.0 case study. The use case describes an integration of a robot into a factory in the life cycle phase operation to evaluate, which fastening system is most suitable as a part of taking adaption intelligence of a building to a higher level.

In this study we provide a methodology for the optimal design of water sensor placement in water distribution networks. The optimization algorithm used is based on a simulation-optimization and a single-objective function approach which incorporates multiple factors used in the design of the system. In this sense the proposed model mimics a multiobjective approach and yields the final design without explicitly specifying a preference among the multiple objectives of the problem. A reliability constraint concept is also introduced into the optimization model such that the minimum number of sensors and their optimal placement can be identified in order to satisfy a prespecified reliability criterion for the network. Progressive genetic algorithm approach is used for the solution of the model. The algorithm works on a subset of the complete set of junctions present in the system and the final solution is obtained through the evolution of subdomain sets. The proposed algorithm is applied to the two test networks to assess the selected design. The results of the proposed solution are discussed comparatively with the outcome of other solutions that were submitted to a water distribution systems analysis symposium. These comparisons indicate that the algorithm proposed here is an effective approach in solving this problem.

In the assessment of principles and guidelines to achieve specific goals before strategies in water resources and related sectors are formulated, the quality of experts participating in making group decisions should be evaluated. This paper introduces an innovative approach designed to evaluate the quality of group members based on their consistency and deviations from the group's decision. The group members are considered as alternatives within a multi-criteria framework, employing several typical performance indicators as criteria to assess their competence and compliance with the group. Considering the policy-making, the paper provides a rationale for possibly excluding certain members from the decision-making process to prevent making unsustainable decisions. A case study is presented about the evaluation of the importance of six Ramsar sites in Serbia, facing imminent threats from water regime disturbances and climate change-induced droughts. Seven experts participated in the process and the results revealed that several experts displayed the poorest performance across all three prioritization schemes. This suggests the necessity for re-evaluating their judgments or considering their exclusion from the final decision-making process. The proposed assessment procedure holds promise for enhancing the potential to derive sustainable solutions in any complex and critical domain of water resources policy-making and strategic planning.

Water storage reservoirs can be either sustainable or exhaustible. In the absence of sediment management, reservoir storage is an exhaustible resource with long-term consequences. Previous economic planning of reservoirs essentially guaranteed non-sustainable solutions. This paper describes a new economic paradigm for economic assessments of new and existing reservoirs. The new economic paradigm provides a framework for comprehensive accounting of economic benefits and costs over a sufficiently long period of analysis, including cost estimates for dam decommissioning and lost benefits where sediments are not sustainably managed. A case study applies this framework to a hypothetical western US reservoir to quantitatively compare the status quo (i.e., no sediment management) with a selection of sediment management alternatives. Results indicate that sustainable sediment management can be less expensive than the consequences of ignoring sedimentation (e.g., eventual dam decommissioning and replacing lost storage capacity). Additional work shows that beginning sediment management within a decade of reservoir construction prevents the most severe impacts of sedimentation. An investigation of alternative discounting approaches indicates that the approach employed can have a significant impact on economic results.

The Mekong River Basin in Southeast Asia is undergoing rapid development in the exploitation of its water resources. Although hydropower is the most dominant driver for water development, the possibilities for multipurpose reservoirs have been increasingly discussed but not well studied. The authors assess the potential benefits and negative impacts of a multipurpose reservoir cascade facilitating hydropower and irrigation in the Sesan River, a transboundary tributary of the Mekong. A model-based assessment approach was developed where the hydropower operations of a cascade of reservoirs were simulated together with the irrigation water withdrawals. The assessment revealed that the reservoirs created considerable irrigation potential (28,348 ha), and the resulting losses for hydropower generation were relatively small (−1.6%). The river flow impacts were significant, but they originated mainly from the hydropower operations. The inclusion of irrigation led to an increased competition of water resources during the dry season. In addition, the assessed hydropower and irrigation development affected negatively protected areas, agriculturally valuable land, and forest cover. Gaps and shortcomings in the model-based assessments of water resources development were further recognized, including this one, concluding that particularly the connection to ecological and social domains remains often weak and needs, therefore, to be strengthened.

In this study we provide a methodology for the optimal design of water sensor placement in water distribution networks. The optimization algorithm used is based on a simulation-optimization and a single-objective function approach which incorporates multiple factors used in the design of the system. In this sense the proposed model mimics a multiobjective approach and yields the final design without explicitly specifying a preference among the multiple objectives of the problem. A reliability constraint concept is also introduced into the optimization model such that the minimum number of sensors and their optimal placement can be identified in order to satisfy a prespecified reliability criterion for the network. Progressive genetic algorithm approach is used for the solution of the model. The algorithm works on a subset of the complete set of junctions present in the system and the final solution is obtained through the evolution of subdomain sets. The proposed algorithm is applied to the two test networks to assess the selected design. The results of the proposed solution are discussed comparatively with the outcome of other solutions that were submitted to a water distribution systems analysis symposium. These comparisons indicate that the algorithm proposed here is an effective approach in solving this problem.

A key challenge in designing algorithms for leakage detection and isolation in drinking water distribution systems, is the performance evaluation and comparison between methodologies using benchmarks. For this purpose, the "Battle of the Leakage Detection and Isolation Methods" (Bat-tLeDIM) competition was organized in 2020 with the aim to objectively compare the performance of methods for the detection and localization of leakage events, relying on SCADA measurements of flow and pressure sensors installed within a virtual water distribution system. Several teams from academia and the industry submitted their solutions, using various techniques including time-series analysis, statistical methods, machine learning, mathematical programming, meta-heuristics and engineering judgment, and were evaluated using realistic economic criteria. This paper summarizes the results of the competition and conducts an analysis of the different leakage detection and isolation methods used by the teams. The competition results highlight the need for further development of methods for leakage detection and isolation, and also the need to develop additional open benchmark problems for this purpose.

Many groundwater remediation designs for contaminant plume containment are developed using mathematically based groundwater now models. These mathematical models are most eiTective as predictive tools when the parameters that govern groundwater flow are known with a high degree of certainty. The hydraulic conductivity of an aquifer, however, is uncertain, and so remediation designs developed lIsing models employing one realization of the hydraulic conductivity field have an associated risk of failure of plume containment. To account for model uncertainty attributable to hydraulic conductivity in detennining an optimal groundwater remediation deSign for plume containment, a method of optimization called robust optimization is utilized, This method of optimization is a multi scenario approach whereby mUltiple hydraulic conductivity fields are examined simultaneously. By examining these fields simultaneously, the variability of the uncertainty is included in the model. To increase the efficiency of the robust optimization approach, a sampling technique i.' > developed that allows the modeler to determine the minimum number of field realizations necessary to achievc a reliable remediation design.

Many groundwater remediation designs for contaminant plume containment are developed using mathematically based groundwater now models. These mathematical models are most eiTective as predictive tools when the parameters that govern groundwater flow are known with a high degree of certainty. The hydraulic conductivity of an aquifer, however, is uncertain, and so remediation designs developed lIsing models employing one realization of the hydraulic conductivity field have an associated risk of failure of plume containment. To account for model uncertainty attributable to hydraulic conductivity in detennining an optimal groundwater remediation deSign for plume containment, a method of optimization called robust optimization is utilized, This method of optimization is a multi scenario approach whereby mUltiple hydraulic conductivity fields are examined simultaneously. By examining these fields simultaneously, the variability of the uncertainty is included in the model. To increase the efficiency of the robust optimization approach, a sampling technique i.' > developed that allows the modeler to determine the minimum number of field realizations necessary to achievc a reliable remediation design.

Best Management Practices (BMPs) have become the most effective way to mitigate non-point source pollution (NPS) issues. Much attention has been paid to NPS in rural areas, where agricultural activities increase nutrients, toxics, and sediments in surface water. Stormwater from urban areas is also a major contributor to NPS pollution.

The filling or the pressurizing of closed pipes used to collect water, to transfer it, to evacuate it or its bringing from a tank implies an evolution of the water head which will be assimilated to a hydraulic jump in the first phase .This jump is characterized by two conjugates heads related thanks to a formulation relating them to the Froude number obtained using a linear regression applied to the experimental results of tests carried on a Plexiglas pipe using a pump for its filling. These heads change in time too until having the value of the diameter’s pipe or exceeding it .this phenomena makes transition between different types of flow and three states will be observed: a free surface section, a full section no pressurized and a pressurized one. The relationship which we have obtained presents a good correlation but it is different from the Belanger’s one addressed to rectangular shape of channels. In this study we hope that we will contribute to explain this complicated passag...

A market-based water supply problem is modeled as an optimization problem maximizing net benefit from water use such that all the concerned parties use an economically optimal allocation considering damages due to total dissolved solids (TDS) and institutional constraints. These institutional constraints include water supply requirements under international treaty and historical allocations of water to agriculture. The income from water in municipal use, based on the concept of consumer surplus, is utilized in the objective function along with benefit from agricultural uses, supply costs, and damage costs due to poor quality water, which are estimated using available data. The research assesses the impact that system-wide optimal allocation of water will have in increasing monetary benefits and reducing water salinity levels in terms of TDS along the reach of the Rio Grande from Elephant Butte, New Mexico, to Fort Quitman, Texas. The analysis is performed under three institutional constraints, which include flow regulation at the reservoir, restrictions on trade between states, and allowing trade between the states. Among these scenarios, allowing trade between the states results in the best solution in terms of both net benefit and reducing damage due to poor quality water.

A chance constrained model is presented for the minimum cost design of water distribution networks. This methodology attempts to account for the uncertainties in required demands, required pressure heads, and pipe roughness coefficients. The optimization problem is formulated as a nonlinear progmmmhg model which is solved using a generalized reduced gradient method. Details of the mathematical model formulation are presented along with example applications. Results illustrate that uncertainties in future demands, pressure head requirements, and pipe roughness can have significant effects on the optimd network design and cost. There is currently no universally accepted definition or measure of the reliability of water distribution systems. In general, reliability is defined as the probability that a system performs its mission within specified limits for a given period of time in a specified environment. Over the past two decades, there have been many models developed for the analysis and the minimum cost design of water distribution networks (e.g., Alperovit~ and Shamir 1977; Quindry et al. 1981; Morgan and Goulter 1986; Lansey and Mays 1987). Only a very few models have been reported that attempt to consider the reliability of the water distribution network and the various components. Coals and Goulter (1985) presented three approaches by which the probability of failure of individual pipes can be related to a measure of the overall system reliability in a linear programming minimum cost design procedure. No models explicitly consider the uncertainties in demands, pressure heads, and pipe roughness. The real issue of water distribution system reliability concems the ability of the system to supply the demands at the nodes or demand points within the system at required minimum pressures. The conventional design process for water distribution systems is a trial and emor procedure that attempts to fmd a design that represents a least-cost solution that can satisfy demands. These trial and error methods make no attempt to analyze or define any reliability aspects of the designed system and have no guarantee that the

The objective of this study is to compare the sustainability of current water systems when a dual water distribution system (WDS) is used for the non-potable water purposes of fire protection, irrigation, and toilet flushing. Sustainability of urban WDS is evaluated in terms of hydraulic efficiency and water quality. The first step is to assess sustainability of an example urban WDS by using sustainability index (SI). The SI is measured by reliability, resiliency, and vulnerability performance indices. Pressure and water age are selected as main parameters to determine sustainability. Once the SIs for pressure and water age are calculated by using the extended period simulation in the U.S. Environmental Protection Agency EPANET, these parameters are aggregated into an overall score (SIoverall). The critical areas are identified and improved by either adding network elements (i.e. pumps, valves) or adding a second WDS (i.e. reclaimed WDS) to serve for non-potable water demand. Fire f...

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A hydraulic network model has been constructed by using EPANET program to simulate the water distribution system network of Al-Hakeem Quarter at Maqil district in the Governorate of Basrah. The model is calibrated according to the observed head in 5 junctions. Head at selected junctions is measured by Bourdon gauge. The best results of the model are selected according to a trial and error procedure based on three common statistic coefficients (root mean squared error, standard error, and coefficient of correlation). This model can be used if any changes, such as the addition of elevated tank to the region, addition of another pumping station, or an expansion of the network take place in the future.

In the last decade, leakage has become a high priority to water, oil and sewage transport industries and to the regulators, in order to fulfil legal milestones, to increase the profits of the companies, to protect the environment and to use the best as possible the scarce natural ...

The subject of this paper is the analysis of a very common problem of water distribution systems of cities in Poland, which is the concentration of chlorine in water supply networks and the economic aspects of electricity consumption for the supply of pumps. As an example of the analysis, the water distribution system model of Łapy and the available data from the years 2015-2017 was used. As part of the work, an assessment of the existing state of the city water distribution system of Łapy was presented (lying in the Bialystok poviat), conducted with the help of the EPANET computer program, and aimed at improving the efficiency of the examined network. This allowed us to avoid errors during the investment and to assess the condition of the water supply network. This program was chosen because it is publicly available, as well as used by many companies to solve problems with water supply systems in a friendly and clear way.

Water distribution systems are constructed to supply water for domestic, industrial and commercial consumers. The design, operation and management of these distribution systems is usually supported by the application of hydraulic models, which are built to replicate the behavior of real systems. Conventional demand driven models simulate flows and pressures of a water distribution system requiring assumptions of known demands and known valve statuses. Due to the stochastic behavior of the water demands as well as the complexity of the piping network, these assumptions usually lead to an inadequate understanding of the full range of operational states in the water system. Installation of sensor devices in a network can provide information about some components in the system. However, calibration of the water demands and identification of valve statuses is either still not feasible or very difficult being attributable to the usual limited number of available measurement devices in most real water networks. This dissertation addresses three main issues of water distribution modelling, which include: (1) calibration of water demands under ill-posed conditions where the number of measurements is less than the number of parameter variables, (2) estimation of water demands under uncertainty in a near real-time context, and (3) calibration and localization of unknown partially/fully closed valves in a water network. The solutions for these problems, which are the main contributions of the research, are described by three journal papers included in this dissertation. The first journal paper presents a novel approach to calibration of the water demand multipliers under ill-posed (i.e. underdetermined) conditions by the multiple runs of a Genetic Algorithm model. The results from three case studies show that the average values of multiple runs of the Genetic Algorithm model can deliver very good estimates of the water demand multipliers, the flow rates and nodal heads at non-measured locations with a limited number of the measurements. In addition, the effects of the location and the number of measurement sites to the output of the demand calibration model are also analysed in the paper.

The Philadelphia Water Department developed a unique, Web-based water quality forecasting system for the Schuylkill River called RiverCast. Based on real-time turbidity, flow, and rainfall data, it provides up-to-the-hour public service information on the estimated current fecal coliform concentrations in the river and the acceptable types of recreation based on those conditions. The system is designed to maximize accuracy while avoiding recommendations that suggest water quality is better than it is likely to be ͑avoidance of false positives͒. RiverCast can be reached on the Web at www.phillyrivercast.org.

The Philadelphia Water Department developed a unique, Web-based water quality forecasting system for the Schuylkill River called RiverCast. Based on real-time turbidity, flow, and rainfall data, it provides up-to-the-hour public service information on the estimated current fecal coliform concentrations in the river and the acceptable types of recreation based on those conditions. The system is designed to maximize accuracy while avoiding recommendations that suggest water quality is better than it is likely to be ͑avoidance of false positives͒. RiverCast can be reached on the Web at www.phillyrivercast.org.

Optimal operation of a water supply system is solved by progressive optimality (PO), an iterative dynamic programming (DP) method. Given the forecasted demands for the coming 24 hr, the initial and final conditions in the reservoirs, the hydraulic properties of all system components, and the variable energy cost over the day, an optimal schedule of pump operation is found. The algorithm cycles iteratively over the time steps (hours of the day) and network subsystems, and converges to the optimum from any (feasible or infeasible) initial solution. The global optimum is guaranteed only under certain conditions; otherwise a local optimum may be reached. The method is developed and demonstrated on a regional water supply system with eight reservoirs and seven pumping stations. 'Head, Dept. of Real-Time Control for Water Systems, Texel Electronics, 37 Petach Tikva Rd.

In this study, three different stormwater control measures (SCMs) pollutant removal models, consisting of the linear regression model, modified Fair and Geyer (MFG) model, and k-C Ã model, were simulated under both steady-state and dynamic hydraulic conditions to evaluate how applying those models to a dynamic modeling framework will affect pollutant removal outputs. Uncertainty of the SCM models was also evaluated using Monte Carlo (MC) and first-order variance estimation (FOVE) approaches. The SCM models were calibrated to data from the International Stormwater Best Management Practices (BMP) database assuming steady-state hydraulic conditions for each event, then applied to the dynamic modeling framework with variable hydraulic conditions dictated by runoff generated from the dynamic watershed model. The linear regression model generated the same pollutant removal results under both steady-state and dynamic conditions. However, both the MFG and k-C Ã models underestimated pollutant removal by 20%-90% under dynamic modeling conditions. In terms of uncertainty, the FOVE method generated prediction intervals that were smaller than the MC method, with 95th percentile outputs generally being 5%-20% lower using FOVE, compared to MC. The smaller prediction intervals generated by the FOVE method partially compensated for the lower pollutant removal generated by the MFG and k-C Ã models under dynamic modeling conditions, such that the 95th percentile outputs generated using MC and steady-state assumptions were very similar to those generated using FOVE and dynamic modeling.

Access to good quality drinking water is a challenge to the people of Janga who depend on hand-dug wells water for years as the main source of drinking water. This study examined water quality of hand-dug wells in Janga in the West Mamprusi District. A total of ten water samples from five hand-dug wells were collected and analysed for physico-chemical and coliform bacteria quality using standard methods. Generally, the physicochemical parameters varied, but all were within the World Health Organisation standards for portability except turbidity. The study recorded coliform bacteria count that ranged from 0 to 211 cfu/100 ml (total coliform); 0 to 482 cfu/100 ml (faecal coliform); and 0 to 90 cfu/100 ml (Escherichia coli). These exceeded WHO guideline values (0/100 ml) for drinking water indicating that the hand-dug wells are not free from pollution. Coliform bacteria count indicates poor sanitary conditions in Janga, arising from poor handling of domestic wastes, especially garbage and sewage implying water from hand-dug wells is not suitable for direct human consumption. It is therefore recommended that hand-dug wells water should be treated against bacteria before usage in order to meet the millennium development goal 7.

Increasing and changing product requirements demand a permanent readiness for efficient factory adaption. Considering necessary construction adaptions as well as conventional construction planning processes in the context of the factory adaptation process, standard planning methods are unable to support in a fast and efficient way. By application of the BIM method a Building Information Model, which contains all the needed information in one database is generated. BIM is a method for achieving targets, such as selecting the right type of construction technology or building material to evaluate the adaptation measure. The challenges by putting all information in one model are dealing with the amounts of data, identifying data quality and determining the current use case which should be examined. In this publication, the necessary data base is identified and implemented into a Building Information Model to investigate the right fastening system for an Industry 4.0 case study. The use case describes an integration of a robot into a factory in the life cycle phase operation to evaluate, which fastening system is most suitable as a part of taking adaption intelligence of a building to a higher level.