Probabilistic Water Demand Forecasting Using Projected Climatic Data for Blue Mountains Water Supply System in Australia

2014 ◽  
Vol 28 (7) ◽  
pp. 1959-1971 ◽  
Author(s):  
Md Mahmudul Haque ◽  
Ataur Rahman ◽  
Dharma Hagare ◽  
Golam Kibria
Keyword(s):  
Water Supply ◽  
Water Demand ◽  
Demand Forecasting ◽  
Supply System ◽  
Water Supply System ◽  
Climatic Data ◽  
Blue Mountains ◽  
Water Demand Forecasting

scholarly journals Performance Assessment for Short-Term Water Demand Forecasting Models on Distinctive Water Uses in Korea

2021 ◽  
Vol 13 (11) ◽  
pp. 6056
Author(s):  
Kang-Min Koo ◽  
Kuk-Heon Han ◽  
Kyung-Soo Jun ◽  
Gyu-Min Lee ◽  
Jung-Sik Kim ◽  
...  
Keyword(s):  
Water Supply ◽  
Water Consumption ◽  
Water Demand ◽  
Demand Forecasting ◽  
Supply System ◽  
Water Supply System ◽  
Smart Meter ◽  
Short Term ◽  
Water Demand Forecasting ◽  
Smart Water

It is crucial to forecast the water demand accurately for supplying water efficiently and stably in a water supply system. In particular, accurately forecasting short-term water demand helps in saving energy and reducing operating costs. With the introduction of the Smart Water Grid (SWG) in a water supply system, the amount of water consumption is obtained in real-time through a smart meter, which can be used for forecasting the short-term water demand. The models widely used for water demand forecasting include Autoregressive Integrated Moving Average, Radial Basis Function-Artificial Neural Network, Quantitative Multi-Model Predictor Plus, and Long Short-Term Memory. However, there is a lack of research on assessing the performance of models and forecasting the short-term water demand in the SWG demonstration plant. Therefore, in this study, the short-term water demand was forecasted for each model using the data collected from a smart meter, and the performance of each model was assessed. The Smart Water Grid Research Group installed a smart meter in block 112 located in YeongJong Island, Incheon, and the actual data used for operating the SWG demonstration plant were adopted. The performance of the model was assessed by using the Residual, Root Mean Square Error, Normalized Root Mean Square Error, Nash–Sutcliffe Efficiency, and Pearson Correlation Coefficient as indices. As a result of water demand forecasting, it is difficult to forecast water demand only by time and water consumption. Therefore, as the short-term water demand forecasting models using only time and the amount of water consumption have limitations in reflecting the characteristics of consumers, a water supply system can be managed more precisely if other factors (weather, customer behavior, etc.) influencing the water demand are applied.

scholarly journals Performance Assessment for Short-Term Water Demand Forecasting Models at an End-Use Level in Korea

2021 ◽  
Author(s):  
Kang Min Koo ◽  
Kuk Heon Han ◽  
Kyung Soo Jun ◽  
Gyumin Lee ◽  
Jung Sik Kim ◽  
...  
Keyword(s):  
Water Supply ◽  
Water Consumption ◽  
Water Demand ◽  
Demand Forecasting ◽  
Supply System ◽  
Water Supply System ◽  
Short Term ◽  
Water Demand Forecasting ◽  
Smart Water ◽  
End Use

It is crucial to forecast the water demand accurately for supplying water efficiently and stably in a water supply system. In particular, accurately forecasting short-term water demand helps in saving energy and reducing operating costs. With the introduction of the Smart Water Grid (SWG) in a water supply system, the amount of water consumption is obtained in real time through an advanced metering infrastructure (AMI) sensor, which can be used for forecasting the short-term water demand. The models widely used for water demand forecasting include the autoregressive integrated moving average, radial basis function-artificial neural network, quantitative multi-model predictor plus, and long short-term memory. However, there is a lack of research on assessing the performance of models and forecasting the short-term water demand by applying the data on the amount of water consumption by purpose and the pipe diameter of an end-use level of the SWG demonstration plant in each demand forecasting model. Therefore, in this study, the short-term water demand was forecasted for each model using the data collected from the AMI, and the performance of each model was assessed. The Smart Water Grid Research Group installed ultrasonic-wave-type AMI sensors in the block 112 located in YeongJong Island, Incheon, and the actual data used for operating the SWG demonstration plant were adopted. The performance of the model was assessed by using the residual, root mean square error (RMSE), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency (NSE), and Pearson correlation coefficient (PCC) as indices. The water demand forecast was slightly underestimated in models that employed the assessment results based on the RMSE and NRMSE. Furthermore, the forecasting accuracy was low for the NSE due to a large number of negative values; the correlation between the observed and forecasted values of the PCC was not high, and it was difficult to forecast the peak amount of water consumption. Therefore, as the short-term water demand forecasting models using only time and the amount of water consumption have limitations in reflecting the characteristics of consumers, a water supply system can be managed more precisely if other factors (weather, customer behavior, etc.) influencing the water demand are applied.

scholarly journals Sustainability characteristics of drinking water supply

2020 ◽  
Author(s):  
Jolijn van Engelenburg ◽  
Erik van Slobbe ◽  
Adriaan J. Teuling ◽  
Remko Uijlenhoet ◽  
Petra Hellegers
Keyword(s):  
Drinking Water ◽  
Water Supply ◽  
Water Demand ◽  
Supply System ◽  
Water Supply System ◽  
Drinking Water Supply ◽  
Extreme Weather Events ◽  
Water Supply Systems ◽  
Global Issues ◽  
Drinking Water Supply System

Abstract. Developments such as climate change and growing demand for drinking water threaten the sustainability of drinking water supply worldwide. To deal with this threat, adaptation of drinking water supply systems is imperative, not only on a global and national scale, but particularly on a local scale. This investigation sought to establish characteristics that describe the sustainability of local drinking water supply. We use an integrated systems approach, describing the local drinking water supply system in terms of hydrological, technical and socio-economic characteristics that determine the sustainability of a local drinking water supply system. Three cases on drinking water supply in the Netherlands are analysed. One case relates to a short-term development, that is the 2018 summer drought, and two concern long-term phenomena, that is, changes in water quality and growth in drinking water demand. The approach taken recognises that next to extreme weather events, socio-economic developments will be among the main drivers of changes in drinking water supply. Effects of pressures associated with, for example, population growth, industrial developments and land use changes, could result in limited water resource availability, deteriorated groundwater quality and growing water demand. To gain a perspective on the case study findings broader than the Dutch context, the sustainability issues identified were paired with global issues concerning sustainable drinking water supply. This resulted in a proposed set of generally applicable sustainability characteristics, each divided into five criteria describing the hydrological, technical and socio-economic sustainability of a local drinking water supply system. Elaboration of these sustainability characteristics and criteria into a sustainability assessment can provide information on the challenges and trade-offs inherent in the sustainable development and management of a local drinking water supply system.

scholarly journals Analysis of the water meter management of the urban-rural water supply system

2018 ◽  
Vol 44 ◽  
pp. 00051 ◽  
Author(s):  
Joanna Gwozdziej-Mazur ◽  
Kamil Świętochowski
Keyword(s):  
Water Supply ◽  
Water Demand ◽  
Supply System ◽  
Water Supply System ◽  
Water Losses ◽  
Rural Water Supply ◽  
Rural Water ◽  
Urban Rural ◽  
Water Supply Company ◽  
Water Meter

Water losses in the water supply network pose a continuous challenge for water companies. Already during designing new networks, the designer assumes that the amount of water demand must be increased by a certain percentage (usually by 10% of the total average daily water demand for municipal and industrial purposes) due to the possible occurrence of water losses. Water loss is meant the difference between the amount of water injected into the network and the amount of water used and invoiced, i.e. that brings income for the water supply company. Proper water metering management helps to limit water losses. This paper presents analysis of the water meter management of urban-rural water supply system.

Predicting water demand: a review of the methods employed and future possibilities

2019 ◽  
Vol 19 (8) ◽  
pp. 2179-2198 ◽  
Author(s):  
Gustavo de Souza Groppo ◽  
Marcelo Azevedo Costa ◽  
Marcelo Libânio
Keyword(s):  
Artificial Intelligence ◽  
Water Supply ◽  
Water Demand ◽  
Supply And Demand ◽  
Demand Forecasting ◽  
System Management ◽  
Water Demand Forecasting ◽  
Combination Of Methods ◽  
Applications Of Machine Learning

Abstract The balance between water supply and demand requires efficient water supply system management techniques. This balance is achieved through operational actions, many of which require the application of forecasting concepts and tools. In this article, recent research on urban water demand forecasting employing artificial intelligence is reviewed, aiming to present the ‘state of the art’ on the subject and provide some guidance regarding methods and models to research and professional sanitation companies. The review covers the models developed using standard statistical techniques, such as linear regression or time-series analysis, or techniques based on Soft Computing. This review shows that the studies are, mostly, focused on the management of the operating systems. There is, therefore, room for long-term forecasts. It is worth noting that there is no global model that surpasses all the methods for all cases, it being necessary to study each region separately, evaluating the strengths of each model or the combination of methods. The use of statistical applications of Machine Learning and Artificial Intelligence methodologies has grown considerably in recent years. However, there is still room for improvement with regard to water demand forecasting.

Converting scientific research into a practical tool co-designed with the stakeholders in R Shiny: a web-based application for managing the main reservoir of the drinking water supply system in the Romagna region, Italy

2020 ◽  
Author(s):  
Alessio Pugliese ◽  
Mattia Neri ◽  
Armando Brath ◽  
Elena Toth
Keyword(s):  
Drinking Water ◽  
Water Supply ◽  
Water Demand ◽  
Scientific Research ◽  
Supply System ◽  
Water Supply System ◽  
Climate Impacts ◽  
Drinking Water Supply ◽  
Web Based ◽  
Drinking Water Supply System

<p>Complex water optimisation problems represent one of the biggest challenges of the near future due to human and climate impacts. On the one hand, stakeholders in the water supply sector require high-level knowledge of the whole water cycle process at different scales, with the aim to either assess the risk for uncertain future water availability or rely on more analytic approaches for decision making. On the other hand, scientific research produces high quality models, algorithms and schemes capable of solving the water problems, but scientists often struggle when it comes to deploy tools that deliver their research outcomes to stakeholders and decision makers that ultimately will use them. The principal goal of this project is to fill the gap between the development of innovative research methodologies and their practical usability in the real world. We present “RApp”, a web-based application written purely in R within the Shiny framework and developed in collaboration with the water supply company Romagna Acque SpA. RApp simulates and visualizes the behavior of the reservoir that sustains the drinking water supply system of the Romagna region, Italy, in order to support its optimal management. Reservoir simulations are obtained connecting, through a unique and site-specific modelling chain, the inflows from the upstream catchments, the functioning of the reservoir, the potential of the treatment plant and the water demand. The optimized monthly-based management rules were obtained off-line, through a multi-objective optimization algorithm by maximizing the water yields and, at the same time, minimizing the occurrence of water outages during drought periods. The RApp user can produce quick reports of the past and expected reservoir yields and stored volumes, in terms of either graphical or table outputs, as a function of different initial and boundary conditions provided by the users, such as the initial stored volume, the expected inflows, the adoption of optimized or user-defined management rules, the occurrence of an abrupt change in the water demand, thus, allowing stakeholders to explore the impact of different scenarios and management options. For developing the tool, a very close interaction between the research group and the stakeholders was required, and is still ongoing, in order to define and then expand the functionalities of the software that are most needed for its practical use.</p>

scholarly journals Sustainability Assessment of the Water Management System for the Boukan Dam, Iran, Using CORDEX- South Asia Climate Projections

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1723
Author(s):  
Farzad Emami ◽  
Manfred Koch
Keyword(s):  
Water Management ◽  
Water Supply ◽  
South Asia ◽  
Water Demand ◽  
Hydrologic Model ◽  
Supply System ◽  
Water Supply System ◽  
Management Tool ◽  
Climate Projections ◽  
Group Index

The present study aimed to quantify the future sustainability of a water supply system using dynamically-downscaled regional climate models (RCMs), produced in the South Asia Coordinated Regional Downscaling Experiment (CORDEX) framework. The case study is the Boukan dam, located on the Zarrine River (ZR) of Urmia’s drying lake basin, Iran. Different CORDEX- models were evaluated for model performance in predicting the temperatures and precipitation in the ZR basin (ZRB). The climate output of the most suitable climate model under the RCP45 and RCP85 scenarios was then bias-corrected for three 19-year-long future periods (2030, 2050, and 2080), and employed as input to the Soil and Water Assessment Tool (SWAT) river basin hydrologic model to simulate future Boukan reservoir inflows. Subsequently, the reservoir operation/water demands in the ZRB were modeled using the MODSIM water management tool for two water demand scenarios, i.e., WDcurrent and WDrecom, which represent the current and the more sustainable water demand scenarios, respectively. The reliability of the dam’s water supply for different water uses in the study area was then investigated by computing the supply/demand ratio (SDR). The results showed that, although the SDRs for the WDrecom were generally higher than that of the WDcurrent, the SDRs were all <1, i.e., future water deficits still prevailed. Finally, the performance of the water supply system was evaluated by means of risk, reliability, resiliency, vulnerability, and maximum deficit indices, and the combination of the indices to estimate the Sustainability Group Index (SGI). The findings indicated that, compared to the historical period for both the water demand scenarios, WDcurrent and WDrecom, the average SGI of each RCP would be decreased significantly, particularly, for the more extreme RCP85 scenario. However, as expected, the SGI decrease for the WDrecom was less than that of the WDcurrent, indicating the advantage of implementing this more sustainable water demand scenario.

scholarly journals Developing water supply system in Szőgye

2021 ◽  
Author(s):  
Nikolett Fecser ◽  
István Lakatos
Keyword(s):  
Water Management ◽  
Drinking Water ◽  
Water Supply ◽  
Water Consumption ◽  
Water Demand ◽  
Cost Reduction ◽  
Supply System ◽  
Water Supply System ◽  
The Cost

Abstract The deteriorative processes occurring in the environment, the growth of population, the water demand of industry and agriculture, point out day after day the increasing role of water management. The economical use of drinking-water consumption as well as the cost reduction is becoming more and more important. In this research, the measure of a water supplier of Győr was examined in terms of implementing the purposes above.

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