Water demand: the Austrian end-use study and conclusions for the future

2013 ◽  
Vol 14 (2) ◽  
pp. 205-211 ◽  
Author(s):  
Roman Neunteufel ◽  
Laurent Richard ◽  
Reinhard Perfler
Keyword(s):  
Climate Change ◽  
Water Consumption ◽  
Water Demand ◽  
Personal Information ◽  
Residential Buildings ◽  
Meteorological Data ◽  
Age Distribution ◽  
Household Consumption ◽  
Single Family ◽  
End Use

Demographic and climate change will affect in the long term the total water consumption and therefore the planning and management of the related infrastructures. End-use studies provide information on water consumption and its influencing factors. However the availability of such detailed data is very limited. The research project carried out was based on total daily water consumption collected from 12 Austrian water supply areas for periods covering up to 10 years. The general data were complemented with high resolution measurements (ranging from day to 10 second intervals) of household consumption of residential buildings, semi-detached houses, single family homes, and weekend cottages as well as with meteorological data and comprehensive socio-economic and personal information. The major factors influencing residential household consumption are: demographic dynamics; age distribution; household size/family size; living conditions; and regional economic development. In the short term, water consumption is influenced by temperature, precipitation, day of the week and time. For residential consumption, these last parameters were found to be the main causes for the existing peak demands. Modernisation will lead to a further decrease of the indoor per capita water demand. The outdoor demand and its peaks are expected to increase due to climate change.

Developing a demand model integrating end uses of water (DMEUW): structure and process of integration

2015 ◽  
Vol 71 (4) ◽  
pp. 529-537 ◽  
Author(s):  
R. C. Sarker ◽  
S. Gato-Trinidad
Keyword(s):  
Water Consumption ◽  
Water Conservation ◽  
Water Demand ◽  
Daily Rainfall ◽  
Demand Model ◽  
Data Set ◽  
Residential Water Consumption ◽  
End Use ◽  
Hypertext Markup Language ◽  
End Uses

The process of developing an integrated water demand model integrating end uses of water has been presented. The model estimates and forecasts average daily water demand based on the end-use pattern and trend of residential water consumption, daily rainfall and temperature, water restrictions and water conservation programmes. The end-use model uses the latest end-use data set collected from Yarra Valley Water, Australia. A computer interface has also been developed using hypertext markup language and hypertext pre-processor. The developed model can be used by water authorities and water resource planners in forecasting water demand and by household owners in determining household water consumption.

scholarly journals Influência das mudanças climáticas no desempenho térmico de uma habitação com diferentes sistemas construtivos: análise do clima de São Paulo

2020 ◽  
Vol 1 (48) ◽  
pp. 46 ◽  
Author(s):  
Gustavo Henrique Nunes ◽  
Thalita Gorban Ferreira Giglio
Keyword(s):  
Climate Change ◽  
Meteorological Data ◽  
Thermal Capacity ◽  
Sao Paulo ◽  
São Paulo ◽  
Single Family ◽  
Climate Change Effects ◽  
Building Facades ◽  
Building Systems ◽  
Energetic Performance

<p>The thermo-energetic performance of the building is closely related to its climate and, therefore, the effects of climate change can influence the environmental comfort of dwellings over the years. This research aimed to investigate the thermal performance of single-family houses built in different building systems under the influence of the climate change effects on the climate in São Paulo. For this purpose, simulations with EnergyPlus were performed considering four climatic periods: TRY (1954), 2020, 2050 and 2080. The future climate files were generated with the assistance of the CCWorldWeatherGen tool, and the progression generated for the 2020 period was compared with meteorological data measured from 2011 to 2018. The results showed that outdoor air temperature of São Paulo will increase on average of 4.23 °C up to 2100, which will cause the degree-hours for heating (GHA) indicator to decrease to 1.165,24 °Ch and the degree-hours for cooling (GHR) indicator to increase to 144,26 °Ch, according to the constructive system. Furthermore, it was observed that building façades with higher thermal capacity will be important to satisfy the user’s thermal comfort requirements. Therefore, it is necessary to consider climate change in energy efficiency solutions in buildings.</p>

scholarly journals Non-residential water demand model validated with extensive measurements

2012 ◽  
Vol 5 (1) ◽  
pp. 455-471
Author(s):  
E. J. Pieterse-Quirijns ◽  
E. J. M. Blokker ◽  
E. van der Blom ◽  
J. H. G. Vreeburg
Keyword(s):  
Water Demand ◽  
Cold Water ◽  
Residential Buildings ◽  
Water System ◽  
Hot Water ◽  
Demand Model ◽  
Water Heater ◽  
Peak Demand ◽  
Design Rules ◽  
End Use

Abstract. Existing guidelines related to the water demand of non-residential buildings are outdated and do not cover hot water demand for the appropriate selection of hot water devices. Moreover, they generally overestimate peak demand values required for the design of an efficient and reliable water system. Recently, a procedure was developed based on the end-use model SIMDEUM® to derive design rules for peak demand values of both cold and hot water during various time steps for several types and sizes of non-residential buildings, i.e. offices, hotels and nursing homes. In this paper, the design rules are validated with measurements of cold and hot water patterns on a per second base. The good correlation between the simulated patterns and the measured patterns indicates that the basis of the design rules, the SIMDEUM simulated standardised buildings, is solid. Moreover, the SIMDEUM based rules give a better prediction of the measured peak values for cold water flow than the existing guidelines. Furthermore, the new design rules can predict hot water use well. In this paper it is illustrated that the new design rules lead to reliable and improved designs of building installations and water heater capacity, resulting in more hygienic and economical installations.

Understanding urban residential end uses of water

2011 ◽  
Vol 64 (1) ◽  
pp. 36-42 ◽  
Author(s):  
Shirley Gato-Trinidad ◽  
Niranjali Jayasuriya ◽  
Peter Roberts
Keyword(s):  
Water Consumption ◽  
Water Conservation ◽  
Water Usage ◽  
Single Family ◽  
Washing Machines ◽  
Consumption Data ◽  
Household Water ◽  
Family Home ◽  
End Use ◽  
End Uses

The ‘end use’ of water is a breakdown of the total household water usage such as water used for toilets, showers, washing machines, taps, lawn watering, etc. Understanding end uses of water will enable water planners, water authorities and household owners determine where water is used/wasted, how much and how often. This paper describes the end uses of water from a number of single-family homes in Greater Melbourne, Australia. The study involves the analysis of water consumption data recorded at 5-s intervals from logged households collected by Yarra Valley Water in Melbourne in 2004. The study determines how much water is used for outdoor and indoor purposes in a single-family home in Melbourne and compares the water usage during winter and summer. Hourly patterns of major end uses of water are also developed. The aim of this study is to improve the understanding of the end uses of water and to assist where to focus water conservation efforts that would be most effective financially and environmentally, and be acceptable to everyone.

scholarly journals Macroeconomic Accounting of Water Resources: An Input-Output Approach to Linkage Analysis and Impact Indicators Applied to the State of Ceará, Brazil

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 869
Author(s):  
Rogério Barbosa Soares ◽  
Samiria Maria Oliveira da Silva ◽  
Francisco de Assis de Souza Filho ◽  
Witalo de Lima Paiva
Keyword(s):  
Water Consumption ◽  
Water Demand ◽  
Water Security ◽  
Household Consumption ◽  
Joint Analysis ◽  
Intermediate Water ◽  
Input Output ◽  
Economic Sectors ◽  
Agriculture Sector ◽  
Water Flows

This work aims to identify the key sectors of the economic structure, considering their water flows, and estimate each sector’s impact. The goal is to highlight systemic characteristics in the regional economy, establish water use priorities, and assess water security. Based on a regional input-output matrix, we use the following methodologies: the Rasmussen and Hirschman indices for the ‘forward and backward linkages’; simple multipliers of production, job, and income; and the elasticity of water consumption to final water demand. Thirty-two economic sectors and household consumption are analysed. From the elasticity of final water demand, we find that both trade and household consumption put more pressure on water consumption. Furthermore, a joint analysis of the applied methodologies shows that: (a) the trade sector is more relevant for the linkage of water flows, (b) the agriculture sector has the highest direct water consumption, and (c) the public administration sector has the highest intermediate water consumption.

ANN versus SARIMA models in forecasting residential water consumption in Tunisia

2013 ◽  
Vol 3 (3) ◽  
pp. 330-340 ◽  
Author(s):  
Maamar Sebri
Keyword(s):  
Neural Networks ◽  
Water Consumption ◽  
Water Demand ◽  
Total Water ◽  
Forecasting Accuracy ◽  
The Neural Network ◽  
Household Water ◽  
Residential Water Consumption ◽  
End Use ◽  
Total Water Demand

Water scarcity and increasing water demand, especially for residential end-use, are major challenges facing Tunisia. The need to accurately forecast water consumption is useful for the planning and management of this natural resource. In the current study, quarterly time series of household water consumption in Tunisia was forecast using a comparative analysis between the traditional Box–Jenkins method and an artificial neural networks approach. In particular, an attempt was made to test the effectiveness of data preprocessing, such as detrending and deseasonalization, on the accuracy of neural networks forecasting. Results indicate that the traditional Box–Jenkins method outperforms neural networks estimated on raw, detrended, or deseasonalized data in terms of forecasting accuracy. However, forecasts provided by the neural network model estimated on combined detrended and deseasonalized data are significantly more accurate and much closer to the actual data. This model is therefore selected to forecast future household water consumption in Tunisia. Projection results suggest that by 2025, water demand for residential end-use will represent around 18% of the total water demand of the country.

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&ndash;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.

Stochastic simulation model of water demand in residential buildings

2019 ◽  
Vol 41 (5) ◽  
pp. 544-560
Author(s):  
Tiago de VG Ferreira ◽  
Orestes M Goncalves
Keyword(s):  
Flow Rate ◽  
Water Consumption ◽  
Water Demand ◽  
Distribution Systems ◽  
Water Distribution ◽  
Residential Buildings ◽  
Water Distribution Systems ◽  
Simulation Models ◽  
System Components ◽  
Stochastic Simulation Model

Over the years, researchers have been conducting studies to investigate the water consumption profile in buildings; these studies have contributed to the accumulation of knowledge regarding the correct sizing of hydraulic systems in buildings. In the context of the methods for the characterization of system demand or loading values, the procedures commonly employed to obtain the project flow rate were primarily proposed in the mid-20th century. These models require revision and adaptation to the current water consumption values. In recent years, certain researchers have proposed simulation models with an application focus on water distribution systems owing to the random and temporal behavior of water demand in this system type. In this study, a water-demand stochastic simulation model in residential buildings is proposed, which encompasses the behavioral modelling of users and their interaction with the system to improve the design process of water distribution systems. Therefore, geographical and population factors (quantity, distribution, and organization) were considered for the behavioral modelling of users; regarding the system modelling, aspects related to the hydraulic system were considered, such as the relation between system components, the type of sanitary appliance, and the number of available devices. Different simulations—with several different types of showers—were conducted using the proposed model. Comparing the flows obtained from the simulation and from the Brazilian standard, for all system components, the decrease in the project flow rate varied from 4% to 61%. In terms of material consumption regarding the pipe (PVC), the decrease varied from 25% to 63%. Practical application: When assessing potential designs for components in water distribution systems in buildings robust information is required for water demand across different time scales. The use of simulation models represents an important advance for the dimensioning process of these components, since it is possible to know a wider range of information about the system demand possibilities. The use of this type of model, as discussed in this article, will equip the designer with an enhanced decision making capacity.

scholarly journals Urban Water Demand Prediction for a City That Suffers from Climate Change and Population Growth: Gauteng Province Case Study

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1885 ◽  
Author(s):  
Salah L. Zubaidi ◽  
Sandra Ortega-Martorell ◽  
Hussein Al-Bugharbee ◽  
Ivan Olier ◽  
Khalid S. Hashim ◽  
...  
Keyword(s):  
Climate Change ◽  
Population Growth ◽  
Water Consumption ◽  
Water Demand ◽  
Search Algorithm ◽  
Water System ◽  
Urban Water ◽  
Ann Model ◽  
Gauteng Province ◽  
The Impact

The proper management of a municipal water system is essential to sustain cities and support the water security of societies. Urban water estimating has always been a challenging task for managers of water utilities and policymakers. This paper applies a novel methodology that includes data pre-processing and an Artificial Neural Network (ANN) optimized with the Backtracking Search Algorithm (BSA-ANN) to estimate monthly water demand in relation to previous water consumption. Historical data of monthly water consumption in the Gauteng Province, South Africa, for the period 2007–2016, were selected for the creation and evaluation of the methodology. Data pre-processing techniques played a crucial role in the enhancing of the quality of the data before creating the prediction model. The BSA-ANN model yielded the best result with a root mean square error and a coefficient of efficiency of 0.0099 mega liters and 0.979, respectively. Moreover, it proved more efficient and reliable than the Crow Search Algorithm (CSA-ANN), based on the scale of error. Overall, this paper presents a new application for the hybrid model BSA-ANN that can be successfully used to predict water demand with high accuracy, in a city that heavily suffers from the impact of climate change and population growth.

Excellent environmental performance of beet sugar production in the Netherlands

2020 ◽  
pp. 161-165
Author(s):  
Bertram de Crom ◽  
Jasper Scholten ◽  
Janjoris van Diepen
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Life Cycle ◽  
Environmental Impact ◽  
Water Consumption ◽  
Environmental Performance ◽  
Cane Sugar ◽  
Sugar Production ◽  
Beet Sugar ◽  
Glucose Syrup

To get more insight in the environmental performance of the Suiker Unie beet sugar, Blonk Consultants performed a comparative Life Cycle Assessment (LCA) study on beet sugar, cane sugar and glucose syrup. The system boundaries of the sugar life cycle are set from cradle to regional storage at the Dutch market. For this study 8 different scenarios were evaluated. The first scenario is the actual sugar production at Suiker Unie. Scenario 2 until 7 are different cane sugar scenarios (different countries of origin, surplus electricity production and pre-harvest burning of leaves are considered). Scenario 8 concerns the glucose syrup scenario. An important factor in the environmental impact of 1kg of sugar is the sugar yield per ha. Total sugar yield per ha differs from 9t/ha sugar for sugarcane to 15t/ha sugar for sugar beet (in 2017). Main conclusion is that the production of beet sugar at Suiker Unie has in general a lower impact on climate change, fine particulate matter, land use and water consumption, compared to cane sugar production (in Brazil and India) and glucose syrup. The impact of cane sugar production on climate change and water consumption is highly dependent on the country of origin, especially when land use change is taken into account. The environmental impact of sugar production is highly dependent on the co-production of bioenergy, both for beet and cane sugar.

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