Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID ▲ Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-4601 article 2015 Lee, Jay and Lee, Jay and Lee, Jay and Lee, Jay and Bagheri, Behrad and Bagheri, Behrad and Kao, Hung-An and Kao, Hung-An A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems Manufacturing letters 10.1016/j.mfglet.2014.12.001
publications-4602 article 2015 Nguyen, Khoi and Nguyen, Khoi Anh and Nguyen, Khoi and Nguyen, Khoi and Nguyen, Khoi Anh and Stewart, Rodney Anthony and Stewart, Rodney Anthony and Zhang, Hong and Zhang, Hong and Jones, Christopher and Jones, Christopher Intelligent autonomous system for residential water end use classification Applied Soft Computing 10.1016/j.asoc.2015.03.007 Smart metering technology enables the capture of high resolution water consumption data.Intelligent algorithms autonomously categorise single and combined water end use events.Hybrid combination of HMM, ANN and DTW for pattern recognition problem.Expert system developed to autonomously disaggregate water use into end use categories. Over half of the world's population will live in urban areas in the next decade, which will impose significant pressure on water security. The advanced management of water resources and their consumption is pivotal to maintaining a sustainable water future. To contribute to this goal, the aim of this study was to develop an autonomous and intelligent system for residential water end-use classification that could interface with customers and water business managers via a user-friendly web-based application. Water flow data collected directly from smart water metres connected to dwellings includes both single (e.g., a shower event occurring alone) and combined (i.e., an event that comprises several overlapping single events) water end use events. The authors recently developed an intelligent application called Autoflow which served as a prototype tool to solve the complex problem of autonomously categorising residential water consumption data into a registry of single and combined events. However, this first prototype application achieved overall recognition accuracy of 85\%, which is not sufficient for a commercial application. To improve this accuracy level, a larger dataset consisting of over 82,000 events from over 500 homes in Melbourne and South-east Queensland, Australia, were employed to derive a new single event recognition method employing a hybrid combination of Hidden Markov Model (HMM), Artificial Neural Networks (ANN) and the Dynamic Time Warping (DTW) algorithm. The classified single event registry was then used as the foundations of a sophisticated hybrid ANN-HMM combined event disaggregation module, which was able to strip apart concurrently occurring end use events. The new hybrid model's recognition accuracy ranged from 85.9\% to 96.1\% for single events and 81.8-91.5\% for combined event disaggregation, which was a 4.9\% and 8.0\% improvement, respectively, when compared to the first prototype model. The developed Autoflow tool has far-reaching implications for enhanced urban water demand planning and management, sustained customer behaviour change through more granular water conservation awareness, and better customer satisfaction with water utility providers.
publications-4603 article 2016 Beal, Cara and Beal, Cara and Beal, Cara and Beal, Cara and Gurung, Thulo Ram and Gurung, Thulo Ram and Gurung, Thulo Ram and Stewart, Rodney Anthony and Gurung, Thulo Ram and Stewart, Rodney Anthony and Stewart, Rodney Anthony and Stewart, Rodney Anthony Demand-side management for supply-side efficiency: Modeling tailored strategies for reducing peak residential water demand Sustainable Production and Consumption 10.1016/j.spc.2015.11.005 Abstract Increasingly, the water sector is exploring the value of applying demand management strategies to reduce peak water use through behavioural and technical solutions. Literature suggests that using behavioural interventions may be a useful approach in changing the daily peak demand patterns to reduce the pressure on network pumping energy costs during peak use times. There is a lack of studies, however, that have investigated the role of social based marketing or behavioural intervention studies on specifically reducing and shifting residential peak diurnal daily water end-use demand. This concept is modelled in this current study through the application of longitudinal experimental end-use data to predict how reduced demand through behaviour change can impact on overall peak residential demand. Notwithstanding the acknowledged limitations of the study, results illustrate a range of potential peak hour flow savings that can be realised from reducing total demand, or shifting the peak demand in households. The study provides preliminary evidence that water businesses can use demand-side strategies to also achieve efficiencies in the distribution of urban water (e.g. reduced energy for pumping in pressurised water system, pipe augmentation deferrals, peak energy demands).
publications-4604 article 1987 Su, Yu and Su, Yu Chun and Mays, Larry W. and Mays, Larry W. and Duan, Ning and Duan, Ning and Lansey, Kevin and Lansey, Kevin E Reliability‐Based Optimization Model for Water Distribution Systems Journal of Hydraulic Engineering 10.1061/(asce)0733-9429(1987)113:12(1539) This paper presents the basic framework for a model that can be used to determine the optimal (least‐cost) design of a water distribution system subject to continuity, conservation of energy, nodal head bounds, and reliability constraints. Reliability is defined as the probability of satisfying nodal demands and pressure heads for various possible pipe failures (breaks) in the water distribution system. The overall model includes three that are linked: a steady‐state simulation model, a reliability model, and an optimization model. The simulation model is used to implicitly solve the continuity and energy constraints and is used in the reliability model to define minimum cut sets. The reliability model, which is based on a minimum cut‐set method, determines the values of system and nodal reliability. The optimization model is based on a generalized reduced‐gradient method. Examples are used to illustrate the model.
publications-4605 article 1994 Eiger, Gideon and Eiger, Gideon and Shamir, Uri and Shamir, Uri and Ben‐Tal, Aharon and Ben-Tal, Aharon Optimal design of water distribution networks Water Resources Research 10.1029/94wr00623 Optimal design of a water distribution network is formulated as a two-stage decomposition model. The master (outer) problem is nonsmooth and nonconvex, while the inner problem is linear. A semi-infinite linear dual problem is presented, and an equivalent finite linear problem is developed. The overall design problem is solved globally by a branch and bound algorithm, using nonsmooth optimization and duality theory. The algorithm stops with a solution and a global bound, such that the difference between this bound and the true global optimum is within a prescribed tolerance. The algorithm has been programmed and applied to a number of examples from the literature. The results demonstrate its superiority over previous methods.
publications-4606 article 1988 Wagner, Janet M. and Wagner, Janet M. and Shamir, Uri and Shamir, Uri and Marks, David H. and Marks, David H. Water Distribution Reliability: Analytical Methods Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(1988)114:3(253) Probabilistic reliability measures for the performance of water distribution networks are developed and analytical methods for their computation explained. The paper begins with a review of reliability considerations and measures for water supply systems, making use of similar notions in other fields. It classifies reliability analyses according to the level of detail with which the water system is modeled, and then concentrates on methods relevant to networks. Two probabilistic measures, reachability and connectivity, are explored for use in water distribution systems. Two algorithms for their computation are presented, one for series-parallel networks and one for general networks. These measures are computed for two systems, each with ten nodes. Additionally, the probability that a given point receives sufficient supply is proposed for use as a reliability measure. An algorithm is presented for the calculation of this measure, which combines a capacitated network algorithm with a method to efficiently search through network configurations involving multiple link failures. This measure is calculated for the two sample systems.
publications-4607 article 0 Xu, Chengchao and Xu, Chengchao and Goulter, I. C. and Goulter, Ian C. Reliability-Based Optimal Design of Water Distribution Networks Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(1999)125:6(352) A new approach for reliability-based optimization of water distribution networks is presented. The approach is capable of recognizing the uncertainty in nodal demands and pipe capacity as well as the effects of mechanical failure of system components. A probabilistic hydraulic model is used in the model to account for uncertainty in nodal demands and pipe capacity. The primary innovation of the model is the use of a first-order reliability-method-based algorithm to compute approximate values of the capacity reliability of water distribution networks. Capacity reliability is defined as the probability that the nodal demand is met at or over the prescribed minimum pressure for a fixed network configuration under random nodal demands and random pipe roughnesses. The model also incorporates a strategy for identifying the critical nodes on which the reliability constraints are imposed in the cost minimizing step. The computational efficiency of the optimization is shown to be enhanced by deriving the first-order derivatives analytically using a sensitivity-analysis-based technique. The efficiency and capacity of the proposed algorithm are illustrated by application to two sample networks.
publications-4608 article 1989 Bargieła, Andrzej and Hainsworth, G. D. and Bargiela, Andrzej and Hainsworth, Graham D. Pressure and Flow Uncertainty in Water Systems Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(1989)115:2(212) In the monitoring of water distribution systems, the inaccuracy of input data contributes greatly to the inaccuracy of system state estimates calculated from them. It is important, therefore, that the system operators are given not only the values of flows and pressures in the network at any instant of time but also that they have some indication of how reliable these values are. The quantification of the inaccuracy of calculated flows and pressures caused by the input data uncertainty is called here confidence limit analysis. Several confidence limit analysis algorithms are presented. These include a Monte Carlo simulation method, an optimization method, and a sensitivity matrix technique. The performance of these algorithms is assessed in terms of their suitability for real‐time control or design stage applications. Results are presented for a realistic test network.
publications-4609 article 1990 Duan, Ning and Duan, Ning and Mays, Larry W. and Mays, Larry W. and Lansey, Kevin and Lansey, Kevin E Optimal Reliability‐Based Design of Pumping and Distribution Systems Journal of Hydraulic Engineering 10.1061/(asce)0733-9429(1990)116:2(249) A reliability-based optimization model for water-distribution systems has been developed. The model is aimed at the following goals: (1) Design of the pipe network including the number, location, and size of pumps and tanks; (2) design of the pumping system using a reliability-based procedure considering both hydraulic failures of the entire network and mechanical failure of the pumping system; and (3) determination of the optimal operation of the pumps. The optimization problem is a large mixed-integer, nonlinear programming problem that is solved using a heuristic algorithm consisting of a master problem and a subproblem. The master problem is a pure 0–1 integer programming model, and the subproblem is a large nonlinear programming model solved in an optimal control framework. The conservation of flow and energy constraints are solved implicitly for each iteration of the nonlinear optimization procedure using a hydraulic simulation model, and the reliability constraints are also solved implicitly using a reliability model. The nonlinear programming problem is solved using a generalized reduced gradient code.
publications-4610 article 1996 Reddy, P. V. Niranjan and Reddy, P. V. Niranjan and Sridharan, K. and Sridharan, K. and Rao, P. Venugopala and Rao, Ponugoti Vasantha and Rao, P. V. WLS Method for Parameter Estimation in Water Distribution Networks Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(1996)122:3(157) 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.