939 resultados para Water supply networks
Resumo:
With the service life of water supply network (WSN) growth, the growing phenomenon of aging pipe network has become exceedingly serious. As urban water supply network is hidden underground asset, it is difficult for monitoring staff to make a direct classification towards the faults of pipe network by means of the modern detecting technology. In this paper, based on the basic property data (e.g. diameter, material, pressure, distance to pump, distance to tank, load, etc.) of water supply network, decision tree algorithm (C4.5) has been carried out to classify the specific situation of water supply pipeline. Part of the historical data was used to establish a decision tree classification model, and the remaining historical data was used to validate this established model. Adopting statistical methods were used to access the decision tree model including basic statistical method, Receiver Operating Characteristic (ROC) and Recall-Precision Curves (RPC). These methods has been successfully used to assess the accuracy of this established classification model of water pipe network. The purpose of classification model was to classify the specific condition of water pipe network. It is important to maintain the pipeline according to the classification results including asset unserviceable (AU), near perfect condition (NPC) and serious deterioration (SD). Finally, this research focused on pipe classification which plays a significant role in maintaining water supply networks in the future.
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Water service providers (WSPs) in the UK have statutory obligations to supply drinking water to all customers that complies with increasingly stringent water quality regulations and minimum flow and pressure criteria. At the same time, the industry is required by regulators and investors to demonstrate increasing operational efficiency and to meet a wide range of performance criteria that are expected to improve year-on-year. Most WSPs have an ideal for improving the operation of their water supply systems based on increased knowledge and understanding of their assets and a shift to proactive management followed by steadily increasing degrees of system monitoring, automation and optimisation. The fundamental mission is, however, to ensure security of supply, with no interruptions and water quality of the highest standard at the tap. Unfortunately, advanced technologies required to fully understand, manage and automate water supply system operation either do not yet exist, are only partially evolved, or have not yet been reliably proven for live water distribution systems. It is this deficiency that the project NEPTUNE seeks to address by carrying out research into 3 main areas; these are: data and knowledge management; pressure management (including energy management); and the associated complex decision support systems on which to base interventions. The 3-year project started in April of 2007 and has already resulted in a number of research findings under the three main research priority areas (RPA). The paper summarises in greater detail the overall project objectives, the RPA activities and the areas of research innovation that are being undertaken in this major, UK collaborative study. Copyright 2009 ASCE.
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This paper addresses the potential of public water operations in achieving developmental goals such as the Millennium Development Goals, and argues that the public sector has a comparative advantage in developing water services. The global importance of the public sector in urban water supply is examined through a review of current practice in the world's largest cities, including operational presence and distribution and ongoing trends. Empirical evidence shows that, in transition and developing countries, public operators are capable of undergoing successful reform. One explanatory factor is proposed to be the creation through the public sphere of highly interconnected networks among stakeholders. Such accountability networks act as vehicles for the generation and distribution of public knowledge among stakeholders, which in turn inform rational decision making on the reform and management of operations.
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Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.
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Many water-supply systems in South America utilize the waters of the Guarani aquifer at least as part of their networks. However, there is little present knowledge in Brazil of the factors affecting Rn presence in the water supplied for end-users, despite the economic importance of Guarani aquifer. Rn-222 analyzes of 162 water samples were performed at 8 municipalities in São Paulo State, Brazil, with the aim of investigating the major factors affecting its presence in solution. The Rn-222 activity concentration ranged from 0.04 up to 204.9 Bq/L, with three samples exceeding the World Health Organization maximum limit of 100Bq/L. Aeration was confirmed as the most important factor for Rn release, as expected due to its gaseous nature. Accumulation in pipes and stratification in the water column were other significant factors explaining the data obtained in some circumstances. The Rn daughters Ph-214 and Bi-214 were also determined in a set of selected samples and their presence was directly related to the occurrence of Rn dissolved in water. (c) 2008 Elsevier Ltd. All rights reserved.
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Water systems in the Sultanate of Oman are inevitably exposed to varied threats and hazards due to both natural and man-made hazards. Natural disasters, especially tropical cyclone Gonu in 2007, cause immense damage to water supply systems in Oman. At the same time water loss from leaks is a major operational problem. This research developed an integrated approach to identify and rank the risks to the water sources, transmission pipelines and distribution networks in Oman and suggests appropriate mitigation measures. The system resilience was evaluated and an emergency response plan for the water supplies developed. The methodology involved mining the data held by the water supply utility for risk and resilience determination and operational data to support calculations of non-revenue water. Risk factors were identified, ranked and scored at a stakeholder workshop and the operational information required was principally gathered from interviews. Finally, an emergency response plan was developed by evaluating the risk and resilience factors. The risk analysis and assessment used a Coarse Risk Analysis (CRA) approach and risk scores were generated using a simple risk matrix based on WHO recommendations. The likelihoods and consequences of a wide range of hazardous events were identified through a key workshop and subsequent questionnaires. The thesis proposes a method of translating the detailed risk evaluations into resilience scores through a methodology used in transportation networks. A water audit indicated that the percentage of NRW in Oman is greater than 35% which is similar to other Gulf countries but high internationally. The principal strategy for managing NRW used in the research was the AWWA water audit method which includes free to use software and was found to be easy to apply in Oman. The research showed that risks to the main desalination processes can be controlled but the risk due to feed water quality might remain high even after implementing mitigation measures because the intake is close to an oil port with a significant risk of oil contamination and algal blooms. The most severe risks to transmission mains were found to be associated with pipe rather than pump failure. The systems in Oman were found to be moderately resilient, the resilience of desalination plants reasonably high but the transmission mains and pumping stations are very vulnerable. The integrated strategy developed in this study has a wide applicability, particularly in the Gulf area, which may have risks from exceptional events and will be experiencing NRW. Other developing countries may also experience such risks but with different magnitudes and the risk evaluation tables could provide a useful format for further work.
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Background We investigated the geographical variation of water supply and sanitation indicators (WS&S) and their role to the risk of schistosomiasis and hookworm infection in school age children in West Africa. The aim was to predict large-scale geographical variation in WS&S, quantify the attributable risk of S. haematobium, S. mansoni and hookworm infections due to WS&S and identify communities where sustainable transmission control could be targeted across the region. Methods National cross-sectional household-based demographic health surveys were conducted in 24,542 households in Burkina Faso, Ghana and Mali, in 2003–2006. We generated spatially-explicit predictions of areas without piped water, toilet facilities and finished floors in West Africa, adjusting for household covariates. Using recently published helminth prevalence data we developed Bayesian geostatistical models (MGB) of S. haematobium, S. mansoni and hookworm infection in West Africa including environmental and the mapped outputs for WS&S. Using these models we estimated the effect of WS&S on parasite risk, quantified their attributable fraction of infection, and mapped the risk of infection in West Africa. Findings Our maps show that most areas in West Africa are very poorly served by water supply except in major urban centers. There is a better geographical coverage for toilet availability and improved household flooring. We estimated smaller attributable risks for water supply in S. mansoni (47%) compared to S. haematobium (71%), and 5% of hookworm cases could be averted by improving sanitation. Greater levels of inadequate sanitation increased the risk of schistosomiasis, and increased levels of unsafe water supply increased the risk of hookworm. The role of floor type for S. haematobium infection (21%) was comparable to that of S. mansoni (16%), but was significantly higher for hookworm infection (86%). S. haematobium and hookworm maps accounting for WS&S show small clusters of maximal prevalence areas in areas bordering Burkina Faso and Mali smaller. The map of S. mansoni shows that this parasite is much more wide spread across the north of the Niger River basin than previously predicted. Interpretation Our maps identify areas where the Millennium Development Goal for water and sanitation is lagging behind. Our results show that WS&S are important contributors to the burden of major helminth infections of children in West Africa. Including information about WS&S as well as the “traditional” environmental risk factors in spatial models of helminth risk yielded a substantial gain both in model fit and at explaining the proportion of spatial variance in helminth risk. Mapping the distribution of infection risk adjusted for WS&S allowed the identification of communities in West Africa where integrative preventive chemotherapy and engineering interventions will yield the greatest public health benefits.
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This paper presents an approach to modelling the resilience of a generic (potable) water supply system. The system is contextualized as a meta-system consisting of three subsystems to represent the natural catchment, the water treatment plant and the water distribution infrastructure for urban use. An abstract mathematical model of the meta-system is disaggregated progressively to form a cascade of equations forming a relational matrix of models. This allows the investigation of commonly implicit relationships between various operational components within the meta system, the in-depth understanding of specific system components and influential factors and the incorporation of explicit disturbances to explore system behaviour. Consequently, this will facilitate long-term decision making to achieve sustainable solutions for issues such as, meeting a growing demand or managing supply-side influences in the meta-system under diverse water availability regimes. This approach is based on the hypothesis that the means to achieve resilient supply of water may be better managed by modelling the effects of changes at specific levels that have a direct or in some cases indirect impact on higher-order outcomes. Additionally, the proposed strategy allows the definition of approaches to combine disparate data sets to synthesise previously missing or incomplete higher-order information, a scientifically robust means to define and carry out meta-analyses using knowledge from diverse yet relatable disciplines relevant to different levels of the system and for enhancing the understanding of dependencies and inter-dependencies of variable factors at various levels across the meta-system. The proposed concept introduces an approach for modelling a complex infrastructure system as a meta system which consists of a combination of bio-ecological, technical and socio-technical subsystems.
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This paper presents an approach to developing indicators for expressing resilience of a generic water supply system. The system is contextualised as a meta-system consisting of three subsystems to represent the water catchment and reservoir, treatment plant and the distribution system supplying the end-users. The level of final service delivery to end-users is considered as a surrogate measure of systemic resilience. A set of modelled relationships are used to explore relationships between system components when placed under simulated stress. Conceptual system behaviour of specific types of simulated pressure is created for illustration of parameters for indicator development. The approach is based on the hypothesis that an in-depth knowledge of resilience would enable development of decision support system capability which in turn will contribute towards enhanced management of a water supply system. In contrast to conventional water supply system management approaches, a resilience approach facilitates improvement in system efficiency by emphasising awareness of points-of-intervention where system managers can adjust operational control measures across the meta-system (and within subsystems) rather than expansion of the system in entirety in the form of new infrastructure development.
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This paper presents an approach for identifying the limit states of resilience in a water supply system when influenced by different types of pressure (disturbing) forces. Understanding of systemic resilience facilitates identification of the trigger points for early managerial action to avoid further loss of ability to provide satisfactory service availability when the ability to supply water is under pressure. The approach proposed here is to illustrate the usefulness of a surrogate measure of resilience depicted in a three dimensional space encompassing independent pressure factors. That enables visualisation of the transition of the system-state (resilience) between high to low resilience regions and acts as an early warning trigger for decision-making. The necessity of a surrogate measure arises as a means of linking resilience to the identified pressures as resilience cannot be measured directly. The basis for identifying the resilience surrogate and exploring the interconnected relationships within the complete system, is derived from a meta-system model consisting of three nested sub-systems representing the water catchment and reservoir; treatment plant; and the distribution system and end-users. This approach can be used as a framework for assessing levels of resilience in different infrastructure systems by identifying a surrogate measure and its relationship to relevant pressures acting on the system.
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This project was a step forward in developing the scientific basis for a methodology to assess the resilience of water supply systems under the impacts of climate change. The improved measure of resilience developed in this project provides an approach to assess the ability of water supply systems to absorb the pressure due changing climate while sustaining supply, and their speed of recovery in case of failure. The approach developed can be applied to any generic water supply system.
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This research project provides a scientifically robust approach for assessing the resilience of water supply systems, which are critical infrastructure, to impacts of climate change and population growth. An approach for the identification of trigger points that allows timely and appropriate management actions to be taken to avoid catastrophic system failure is an important outcome of this project. In the current absence of a formal method to evaluate the resilience of a water supply system, the approach developed in this study was based on the characterisation of resilience of a water supply system to a range of surrogate measures. Accordingly, a set of indicators are proposed to evaluate system behaviour and logistic regression analysis was used to assess system behaviour under predicted rainfall, storage and demand conditions.
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In ecosystems driven by water availability, plant community dynamics depend on complex interactions between vegetation, hydrology, and human water resources use. Along ephemeral rivers—where water availability is erratic—vegetation and people are particularly vulnerable to changes in each other's water use. Sensible management requires that water supply be maintained for people, while preserving ecosystem health. Meeting such requirements is challenging because of the unpredictable water availability. We applied information gap decision theory to an ecohydrological system model of the Kuiseb River environment in Namibia. Our aim was to identify the robustness of ecosystem and water management strategies to uncertainties in future flood regimes along ephemeral rivers. We evaluated the trade-offs between alternative performance criteria and their robustness to uncertainty to account for both (i) human demands for water supply and (ii) reducing the risk of species extinction caused by water mining. Increasing uncertainty of flood regime parameters reduced the performance under both objectives. Remarkably, the ecological objective (species coexistence) was more sensitive to uncertainty than the water supply objective. However, within each objective, the relative performance of different management strategies was insensitive to uncertainty. The ‘best’ management strategy was one that is tuned to the competitive species interactions in the Kuiseb environment. It regulates the biomass of the strongest competitor and, thus, at the same time decreases transpiration, thereby increasing groundwater storage and reducing pressure on less dominant species. This robust mutually acceptable strategy enables species persistence without markedly reducing the water supply for humans. This study emphasises the utility of ecohydrological models for resource management of water-controlled ecosystems. Although trade-offs were identified between alternative performance criteria and their robustness to uncertain future flood regimes, management strategies were identified that help to secure an ecologically sustainable water supply.
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A theoretical basis is required for comparing key features and critical elements in wild fisheries and aquaculture supply chains under a changing climate. Here we develop a new quantitative metric that is analogous to indices used to analyse food-webs and identify key species. The Supply Chain Index (SCI) identifies critical elements as those elements with large throughput rates, as well as greater connectivity. The sum of the scores for a supply chain provides a single metric that roughly captures both the resilience and connectedness of a supply chain. Standardised scores can facilitate cross-comparisons both under current conditions as well as under a changing climate. Identification of key elements along the supply chain may assist in informing adaptation strategies to reduce anticipated future risks posed by climate change. The SCI also provides information on the relative stability of different supply chains based on whether there is a fairly even spread in the individual scores of the top few key elements, compared with a more critical dependence on a few key individual supply chain elements. We use as a case study the Australian southern rock lobster Jasus edwardsii fishery, which is challenged by a number of climate change drivers such as impacts on recruitment and growth due to changes in large-scale and local oceanographic features. The SCI identifies airports, processors and Chinese consumers as the key elements in the lobster supply chain that merit attention to enhance stability and potentially enable growth. We also apply the index to an additional four real-world Australian commercial fishery and two aquaculture industry supply chains to highlight the utility of a systematic method for describing supply chains. Overall, our simple methodological approach to empirically-based supply chain research provides an objective method for comparing the resilience of supply chains and highlighting components that may be critical.
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The weighted-least-squares method based on the Gauss-Newton minimization technique is used for parameter estimation in water distribution networks. The parameters considered are: element resistances (single and/or group resistances, Hazen-Williams coefficients, pump specifications) and consumptions (for single or multiple loading conditions). The measurements considered are: nodal pressure heads, pipe flows, head loss in pipes, and consumptions/inflows. An important feature of the study is a detailed consideration of the influence of different choice of weights on parameter estimation, for error-free data, noisy data, and noisy data which include bad data. The method is applied to three different networks including a real-life problem.