Calibration Of Water Distribution Networks Research Articles

Water distribution network calibration for unreported leak localization with consideration of uncertainties

Water distribution network calibration for unreported leak localization with consideration of uncertainties

Challenges in calibration of water distribution network: a case study of Ramnagar Elevated Service Reservoir command area in Nagpur City, India

Abstract Calibration of a hydraulic model is a challenging task as it considers the involvement of a large number of uncertain parameters. There are some parameters like length and diameter of pipes, for which fairly accurate values can be obtained. As with all hydraulic models, water demands are one of the main parameters that cause the most uncertainty in the model outputs. The calibration of the water demands is usually not feasible, which is attributable to the limited quantity of available measurements in most real water networks. However, some parameters like nodal demands and pipe roughness coefficients are estimated close to the actual values. Various types of valves are used for flow control by throttling. Hence, their setting in the field is also an important input to the model. Having more precise data helps in reducing time and results in better calibration as presented in the case study of one hydraulic zone served from Ramnagar Elevated Service Reservoir (ESR) (Zone II) in Nagpur City, Maharashtra State, India. This paper aims at presenting the complexities and challenges involved in calibration of the study area. It further describes the entire process from collection of the required data to the calibration of the network.

Calibration of water distribution network of the Ramnagar zone in Nagpur City using online pressure and flow data

Calibration of hydraulic model of a water distribution network is required to match the model results of flows and pressures with those obtained in the field. This is a challenging task considering the involvement of a large number of parameters. Having more precise data helps in reducing time and results in better calibration as shown herein with a case study of one hydraulic zone served from the Ramnagar Ground Service Reservoir in Nagpur City. Flow and pressure values for the entire day were obtained through data loggers. Network details regarding pipe lengths, diameters, installation year and material were obtained with the largest possible accuracy. Locations of consumers on the network were noted and average nodal consumptions were obtained from the billing records. The non-revenue water losses were uniformly allocated to all junctions. Valve positions and their operating status were noted from the field and used. The pipe roughness coefficients were adjusted to match the model values with field values of pressures at observation nodes by minimizing the sum of square of difference between them. This paper aims at describing the entire process from collection of the required data to the calibration of the network.

Calibration Model for Water Distribution Network Using Pressures Estimated by Artificial Neural Networks

The success of hydraulic simulation models of water distribution networks is associated with the ability of these models to represent real systems accurately. To achieve this, the calibration phase is essential. Current calibration methods are based on minimizing the error between measured and simulated values of pressure and flow. This minimization is based on a search of parameter values to be calibrated, including pipe roughness, nodal demand, and leakage flow. The resulting hydraulic problem contains several variables. In addition, a limited set of known monitored pressure and flow values creates an indeterminate problem with more variables than equations. Seeking to address the lack of monitored data for the calibration of Water Distribution Networks (WDNs), this paper uses a meta-model based on an Artificial Neural Network (ANN) to estimate pressure on all nodes of a network. The calibration of pipe roughness applies a metaheuristic search method called Particle Swarm Optimization (PSO) to minimize the objective function represented by the difference between simulated and forecasted pressure values. The proposed method is evaluated at steady state and over an extended period for a real District Metering Area (DMA), named Campos do Conde II, and the hypothetical network named C-town, which is used as a benchmark for calibration studies.

Water distribution network quality model calibration: a case study – Ahar

In water distribution network calibration of quality models, bulk and wall decay coefficients are considered to be the adjustable parameters. The bulk decay coefficient is usually gained by using a laboratory bottle test method, but the wall decay coefficient is calibrated with field data of residual chlorine at nodes. This paper aims to present a method to adjust the wall decay coefficients of pipes. A metamodelling approach is developed by the combination of an Ant Colony Optimization (ACO) algorithm and an artificial neural network (ANN) with the EPANET simulator. The proposed method is applied on a two-loop test example and real water distribution network. Results showed that the proposed method can increase the speed of solution 58 times more rapidly than the simple method in the two-loop network. In the real network, the classification based on the average flow velocity produced the best results among all categories, and the classification based on material, diameter, and age of pipes produced the best results among the physical criteria. Also, comparison of results between the measured and calculated data for testing data showed an average error of 3.85% and the calibration model gave good performance.

Leak Detection and Localization through Demand Components Calibration

AbstractSuccess in the application of any model-based methodology (e.g., design, control, supervision) highly depends on the availability of a well-calibrated model. The calibration of water distribution networks needs to be performed online due to the continuous evolution of demands. During the calibration process, background leakages or bursts can be unintentionally incorporated to the demand model and treated as a system evolution (change in demands). This work proposes a leak-detection and localization approach to be coupled with a calibration methodology that identifies geographically distributed parameters. The approach proposed consists in comparing the calibrated parameters with their historical values to assess if changes in these parameters are caused by a system evolution or by the effect of leakage. The geographical distribution allows unexpected behavior of the calibrated parameters (e.g., abrupt changes, trends, etc.) to be associated with a specific zone in the network. The performance of t...

Water distribution network calibration using enhanced GGA and topological analysis

The calibration of hydraulic models of water distribution networks (WDN) is of preeminent importance for their analysis and management. It is usually achieved by solving a constrained optimization problem based on some priors on decision variables and the demand-driven simulation of the entire network, given the observations of some hydraulic status variables (i.e. typically nodal heads and sometimes pipe flows). This paper presents a framework to perform the calibration of pipe hydraulic resistances considering two main issues: (i) the enhancements of WDN simulation models allowing us to simplify network topology with respect to serial nodes/trunks and/or to account for a more realistic representation of distributed demands and (ii) a different formulation of the calibration problem itself. Depending on the available measurements, the proposed calibration strategy reduces the hydraulic simulation model size and can permit the decomposition of the network. On the one hand, such a procedure allows for numerical and computational advantages, especially for large size networks. On the other hand, it allows a prompt analysis of observability of calibration decision variables based on actual observations and might help identifying those pipes (i.e. hydraulic resistances) which are more important for the whole network behaviour.

GISRed 1.0, a GIS-based Tool for Water Distribution Models for Master Plans

GISRed is a customized extension to ArcView® GIS3.2, oriented to modeling and calibration of water distribution networks, and which integrates all capabilities…

New Approach to Water Distribution Network Calibration

A new approach is proposed for calibrating hydraulic network models. This procedure uses a nonlinear optimization algorithm along with a standard, off-the-shelf, network solver. Pipe roughness is adjusted until simulation results agree with the values observed in the field. To achieve realistic calibrated roughness values, the objective is to minimize the sum of the squares of the differences between the calibrated and initial pipe roughness estimates, under a set of constraints determined from a sensitivity matrix. The algorithm is applied to a sample network, and the resulting calibrated network is tested under different loading conditions.