Water Distribution Network Models Research Articles

Model Calibration and Leakage Assessment Applied to a Real Water Distribution Network

The use of water distribution network models depends highly on the confidence that the operators have on them. Models generated automatically from the Geographical Information System using the hydraulic equations integrated in a simulation model [7] are available in most of the water utilities. Once the first simulation results are compared with the available measurements, calibration is required [6]. This paper presents the process of adjusting the original network model of a village called Sant Joan de Vilatorrada network to fit the simulation results with the measurements. The adjustments in the model range from the macroalibration level to the microcalibration level [3]. The macrocalibration process is based on the analysis done by the engineers, and the conclusions are formalised for future use in other networks. Microcalibration is centred in setting the emitter coefficients using Genetic Algorithm optimisation. The results of the work include an adjusted model for decision taking, an assessment of the background leakage and a methodology to be applied in other parts of the network.

Study on Management System of Drainage Network

The advanced intelligent optimization algorithms used in water distribution network model study, currently in the pipe network optimization theory is a new, has great research value and practical value of the subject. This paper proposes a decision-making functions to optimize the drainage network system, by choosing the model using intelligent optimization algorithm for computing the most cost-caliber combination, to achieve the renovation and expansion of urban water supply network technical support.

Smart meters for enhanced water supply network modelling and infrastructure planning

To design water distribution network infrastructure, water utilities formulate daily demand profiles and peaking factors. However, traditional methods of developing such profiles and peaking factors, necessary to carry out water distribution network modelling, are often founded on a number of assumptions on how top-down bulk water consumption is attributed to customer connections and outdated demand information that does not reflect present consumption trends; meaning infrastructure is often unnecessarily overdesigned. The recent advent of high resolution smart water meters allows for a new novel methodology for using the continuous ‘big data’ generated by these meter fleets to create evidence-based water demand curves suitable for use in network models. To demonstrate the application of the developed method, high resolution water consumption data from households fitted with smart water meters were collected from the South East Queensland and Hervey Bay regions in Australia. Average day (AD), peak day (PD) and mean day maximum month (MDMM) demand curves, often used in water supply network modelling, were developed from the herein created methodology using both individual end-use level and hourly demand patterns from the smart meters. The resulting modelled water demand patterns for AD, PD and MDMM had morning and evening peaks occurring earlier and lower main peaks (AD: 12%; PD: 20%; MDMM: 33%) than the currently used demand profiles of the regions’ water utility. The paper concludes with a discussion on the implications of widespread smart water metering systems for enhanced water distribution infrastructure planning and management as well as the benefits to customers.

Pump schedules optimisation with pressure aspects in complex large-scale water distribution systems

Abstract. This paper considers optimisation of pump and valve schedules in complex large-scale water distribution networks (WDN), taking into account pressure aspects such as minimum service pressure and pressure-dependent leakage. An optimisation model is automatically generated in the GAMS language from a hydraulic model in the EPANET format and from additional files describing operational constraints, electricity tariffs and pump station configurations. The paper describes in details how each hydraulic component is modelled. To reduce the size of the optimisation problem the full hydraulic model is simplified using module reduction algorithm, while retaining the nonlinear characteristics of the model. Subsequently, a nonlinear programming solver CONOPT is used to solve the optimisation model, which is in the form of Nonlinear Programming with Discontinuous Derivatives (DNLP). The results produced by CONOPT are processed further by heuristic algorithms to generate integer solution. The proposed approached was tested on a large-scale WDN model provided in the EPANET format. The considered WDN included complex structures and interactions between pump stations. Solving of several scenarios considering different horizons, time steps, operational constraints, demand levels and topological changes demonstrated ability of the approach to automatically generate and solve optimisation problems for a variety of requirements.

Testing linear solvers for global gradient algorithm

Steady-state Water Distribution Network models compute pipe flows and nodal heads for assumed nodal demands, pipe hydraulic resistances, etc. The nonlinear mathematical problem is based on energy and mass conservation laws which is solved by using global linearization techniques, such as global gradient algorithm (GGA). The matrix of coefficients of the linear system inside GGA belongs to the class of sparse, symmetric and positive definite. Therefore a fast solver for the linear system is important in order to achieve the computational efficiency, especially when multiple runs are required. This work aims at testing three main strategies for the solution of linear systems inside GGA. The tests are performed on eight real networks by sampling nodal demands, considering the pressure-driven and demand-driven modelling to evaluate the robustness of solvers. The results show that there exists a robust specialized direct method which is superior to all the other alternatives. Furthermore, it is found that the number of times the linear system is solved inside the GGA does not depend on the specific solver, if a small regularization to the linear problem is applied, and that pressure-driven modelling requires a greater number which depends on the size and topology of the network and not only on the level of pressure deficiency.

Water Distribution Network's Modeling and Calibration. A Case Study based on Scarce Inventory Data

This paper focuses on modeling and calibration of a small and poorly documented (portion of the) water distribution network (WDN) that shows pressure problems. Field campaigns are conducted to reduce the inaccuracies found in the inventory's drawings and to aid building a first WDN model. A trial and error procedure was then used to produce successive refinements for the desirable WDN's model fit. The paper describes the path followed through the first model to the final calibrated model, including WDN's instrumentation, the definition of network zones and the measures taken to deal with the pressure problems.

Optimisation of Pump and Valve Schedules in Complex Large-scale Water Distribution Systems Using GAMS Modelling Language

This paper considers optimisation of pump and valve schedules in complex large-scale water distribution networks (WDN). An optimisation model is automatically generated in GAMS language from a hydraulic model in EPANET format and from additional files describing operational constraints, electricity tariffs and pump station configurations. The paper describes how each hydraulic component is modelled. To reduce the size of the optimisation problem the full hydraulic model is simplified using module reduc- tion algorithm, while retaining the nonlinear characteristics of the model. Subsequently, a nonlinear programming solver CONOPT is used to solve the optimisation model. The proposed approached was tested on a large-scale WDN model provided in EPANET format. The considered WDN included complex structures and interactions between pump stations. Solving of several scenarios considering different horizons, time steps, operational constraints and topological changes demonstrated ability of the approach to automatically generate and solve optimisation problems for variety of requirements.

Demand Pattern Calibration in Water Distribution Networks

Water distribution network models are widely used by water companies. Consumer demands are one of the main uncertainties in these models, but their calibration is not feasible due to the low number of sensors available in most real networks. However, the behaviour of these individual demands can be also calibrated if some a priori information is available. A methodology for calibrating demand patterns based on singular value decomposition (SVD) is presented. Demand stochastic nature is overcome by using multiple data samples. The methodology is applied to two water distribution systems: an academic network and a real network with synthetic data.

Identification of Measurement Points for Calibration of Water Distribution Network Models

Abstract Much importance is given to determining the input data for water distribution system networks, particularly with regard to urban networks, because the design and the management of WDS are based on a verification model. Good calibration of models is required to obtain realistic results. This is possible by the use of a certain number of measurements: flow in pipes and pressure in nodes. The purpose of this paper is to analyze a new model able to provide guidance on the choice of measurement points to obtain the site data. All analyses are carried out firstly on literature networks and then on a real network using a new approach based on sensitivity matrices.

Multivariate Statistical Analysis for Water Demand Modeling

Abstract The actual level of water demand is the driving force behind the hydraulic dynamics in water distribution systems. Consequently, it is crucial to estimate it as accurately as possible in order to result in reliable simulation models. In this paper, a copula-based multivariate analysis has been proposed and used for demand prediction for given return period. The analysis is applied to water consumption data collected in the water distribution network of Palermo (Italy). The approach showed to produce consisted demand patterns and to be a powerful tool to be coupled with water distribution network models for design or analysis problems.

Identification of dichloroacetic acid degrading Cupriavidus bacteria in a drinking water distribution network model

Bacterial community structure and composition of a drinking water network were assessed to better understand this ecosystem in relation to haloacetic acid (HAA) degradation and to identify new bacterial species having HAA degradation capacities. Biofilm samples were collected from a model system, simulating the end of the drinking water distribution network and supplied with different concentrations of dichloroacetic and trichloroacetic acids at different periods over the course of a year. The samples were analysed by culturing, denaturing gradient gel electrophoresis (DGGE) and sequencing. Pipe diameter and HAA ratios did not impact the bacterial community profiles, but the season had a clear influence. Based on DGGE profiles, it appeared that a particular biomass has developed during the summer compared with the other seasons. Among the bacteria isolated in this study, those from genus Cupriavidus were able to degrade dichloroacetic acid. Moreover, these bacteria degrade dichloroacetic acid at 18°C but not at 10°C. The microbial diversity evolved throughout the experiment, but the bacterial community was distinct during the summer. Results obtained on the capacity of Cupriavidus to degrade DCAA only at 18°C but not at 10°C indicate that water temperature is a major element affecting DCAA degradation and confirming observations made regarding season influence on HAA degradation in the drinking water distribution network. This is the first demonstration of the HAA biodegradation capacity of the genus Cupriavidus.

Application of Formal and Informal Bayesian Methods for Water Distribution Hydraulic Model Calibration

Water distribution system model parameter calibration is an important step to obtain a representative system model, such that it may be applied to understand system operational performance, often in real time. However, few approaches have attempted to quantify uncertainty in calibrated parameters, model predictions, and consider the sensitivity of model predictions to uncertain parameters. A probabilistic Bayesian approach is applied to calibrate and quantify uncertainty in the pipe roughness groups of an Epanet2 hydraulic model of a real-life water distribution network. Within the applied Bayesian framework, the relative performance of formal and informal Bayesian likelihoods in implicitly quantifying parameter and predictive uncertainty is considered. Both approaches quantify posterior parameter uncertainty with similar posterior distributions for parameter values (mean and standard deviation). However, the uncertainty intervals identified with the informal likelihood are too narrow, regardless of the behavioral threshold applied to derive these bounds. In contrast, the formal Bayesian approach produces more realistic 95% prediction intervals based on their statistical coverage of the observations. This results as the error model standard deviation is jointly inferred during calibration, which also helps to avoid potential overconditioning of the posterior parameter distribution. However, posterior diagnostic checks reveal that the prediction intervals are not valid at percentiles other than the 95% interval as the assumptions of normality, residual homoscedasticity, and noncorrelation, often assumed in hydraulic model calibration, do no hold. More robust calibration requires the development of error models better suited to the nature of residual errors found in water distribution system models.

Modelo para setorizar redes de distribuição de água baseado nas características das unidades consumidoras

Além dos custos diretos, a ocorrência de rupturas na rede de distribuição de água tem sempre consequências sociais associadas, principalmente pela interrupção do abastecimento de água durante a reparação da infraestrutura. Nesses casos, a setorização da rede torna mais fácil qualquer atividade de manutenção. Porém, além do elevado custo da alocação de válvulas de fechamento, as normas brasileiras sobre setorização das redes dizem respeito apenas a questões técnicas que devem ser obedecidas. Portanto, propõe-se uma setorização que também incorpore a intensidade do impacto gerado pela falta de água em cada trecho da tubulação. Para medir esse impacto é proposto um índice de priorização que agrega as características das unidades consumidoras por meio do método multicritério SMARTER. Assim, desenvolve-se um modelo de setorização para manobra que leva em consideração esse índice, buscando a maximização dos benefícios gerados e a minimização do número de válvulas de fechamento.

Modeling Local Water Storages Delivering Customer Demands in WDN Models

Water distribution network (WDN) models account for customer-demands as water withdrawals concentrated in nodes. Customer- demands can be assumed to be constant or varying with nodal head/pressure entailing demand-driven or pressure-driven simulation, respec- tively. In both cases, the direct connection of customer properties to the hydraulic system is implicitly assumed. Nonetheless, in many technical situations, the service pipe fills a local private storage (e.g., a roof tank or a basement tank) from which the water is actually delivered to customers by gravity or pumping systems. In such contexts, the service pipe fills the local tank by means of a top orifice. Consequently, what is really connected to the hydraulic system is a tank, which is subject to a filling/emptying process while supplying water to customers. Therefore, since modeling this technical situation in WDN analyses is necessary, the paper develops a formulation for nodal water withdrawals in WDN models accounting for the filling/emptying process of inline tanks between the hydraulic network and customers. The formulation is also introduced in a widely used method for steady-state WDN modeling, the global gradient algorithm, and its effectiveness to increase the hydraulic accuracy of results is discussed using a simple case study and a small network. DOI: 10.1061/(ASCE) HY.1943-7900.0000812. © 2014 American Society of Civil Engineers. Author keywords: Tank modeling; Water distribution networks; Hydraulic network modeling; Water distribution network simulation; Extended period simulation.

Two-Tiered Sensor Placement for Large Water Distribution Network Models

AbstractWater distribution network models for large municipalities have tens of thousands of interconnecting pipes and junctions with complex hydraulic controls. Many water security applications, including sensor placement optimization, require detailed simulation of potential contamination incidents. The postsimulation optimization problem can easily exceed memory on standard desktop computers. Large networks can be skeletonized to reduce computation; however, this alters network hydraulics, and therefore sensor placement. The objective of this paper is to evaluate a two-tiered sensor placement approach that combines hydraulic and water quality simulations using all-pipes, or original, network models with subsequent geographic aggregation of time and impact values to reduce memory requirements. The two-tiered approach first places sensors on aggregated regions, then refines the solution to actual nodes in the original model. The two-tiered sensor placement approach is compared to results using the origin...

Online simplification of water distribution network models for optimal scheduling

This paper presents an implementation of an extended simplification algorithm of water distribution network models for the purpose of inclusion in the online optimisation strategy for energy and leakage management in water distribution systems. Whereas the previously proposed reduced model represented accurately the original hydraulic water network characteristics, the energy distribution in the simplified model was not preserved. This could cause a situation where the pump speed required to satisfy specified minimum pressure constraints is different for the reduced model and the original model. This problem has been identified, and an appropriate modification to the simplification algorithm has been introduced. The idea comprises introduction of the energy audit of the water network and the calculation of new minimum service pressure constraints for the simplified model. The approach allows the preservation of both hydraulic and energetic characteristics of the original water network and therefore meets the requirements of the online optimisation strategy. Suitability of the proposed approach is evaluated via a case study. The modern parallel programming implementation allowed water network models consisting of several thousand elements to be reduced within 2 min with an average relative accuracy of less than 2% in terms of tanks flows.

Error Analysis of Some Demand Simplifications in Hydraulic Models of Water Supply Networks

Mathematical modeling of water distribution networks makes use of simplifications aimed to optimize the development and use of the mathematical models involved. Simplified models are used systematically by water utilities, frequently with no awareness of the implications of the assumptions used. Some simplifications are derived from the various levels of granularity at which a network can be considered. This is the case of some demand simplifications, specifically, when consumptions associated with a line are equally allocated to the ends of the line. In this paper, we present examples of situations where this kind of simplification produces models that are very unrealistic. We also identify the main variables responsible for the errors. By performing some error analysis, we assess to what extent such a simplification is valid. Using this information, guidelines are provided that enable the user to establish if a given simplification is acceptable or, on the contrary, supplies information that differs substantially from reality. We also develop easy to implement formulae that enable the allocation of inner line demand to the line ends with minimal error; finally, we assess the errors associated with the simplification and locate the points of a line where maximum discrepancies occur.

Experimental investigation of leak hydraulics

In recent decades the hydraulics of leaks, i.e. the definition of the relationships linking the hydraulic quantities in pipes with leaks, has received increasing attention. On the one hand, the definition of the relationship between the leak outflow and the relevant parameters – e.g. the leak area and shape, the pressure inside the pipe and outside the leak, and the pipe material – is crucial for pressure control and inverse analysis techniques. On the other hand, if the effect of the leakage on the governing equations is not taken into account, i.e. the loss of the flow axial momentum is not considered, significant errors can be introduced in the simulation of water distribution systems. In this paper, the governing equations for a pipe with a leak are derived. The basic equations, obtained within different approaches, are presented in a consistent formulation and then compared with the results of some experimental tests. The leak jet angle and other major features of the results are analysed. The estimated values of the parameters can be used in the water distribution network models when pipes with a diffuse leakage are considered.

Using high performance techniques to accelerate demand-driven hydraulic solvers

Computer models of water distribution networks are commonly used to simulate large systems under complex dynamic scenarios. These models normally use so-called demand-driven solvers, which determine the nodal pressures and pipe flow rates that correspond to specified nodal demands. This paper investigates the use of data parallel high performance computing (HPC) techniques to accelerate demand-driven hydraulic solvers. The sequential code of the solver implemented in the CWSNet library is analysed to understand which computational blocks contribute the most to the total computation time of a hydraulic simulation. The results obtained show that, contrary to popular belief, the linear solver is not the code block with the highest impact on the simulation time, but the pipe head loss computation. Two data parallel HPC techniques, single instruction multiple data (SIMD) operations and general purpose computation on graphics processing units (GPGPU), are used to accelerate the pipe head loss computation and linear algebra operations in new implementations of the hydraulic solver of CWSNet library. The results obtained on different network models show that the use of this techniques can improve significantly the performance of a demand-driven hydraulic solver.

Neyman-Scott-based water distribution network modelling

Residential water demand is one of the most difficult parameters to determine when modelling drinking water distribution networks. It has been proven to be a stochastic process which can be characterised as a series of rectangular pulses having set intensity, duration and frequency. Such parameters can be determined using stochastic models such as the Neyman-Scott rectangular pulse model (NSRPM). NSRPM is based on resolving a non-linear optimisation problem involving theoretical moments of the synthetic demand series (equiprobable) and of the observed moments (field measurements) statistically establishing the measured demand series. NSRPM has been applied to generating local residential demand. However, this model has not been validated for a real distribution network with residential demand aggregation, or compared to traditional methods (which is dealt with here). This paper compares the results of synthetic stochastic demand series (calculated using NSRPM applied to determining pressure and flow rate) to results obtained using traditional simulation methods using the curve of hourly variation in demand and to actual pressure and flow rate measurements. The Humaya sector of Culiacan, Sinaloa, Mexico, was used as study area.