Articles | Volume 10, issue 1
https://doi.org/10.5194/dwes-10-1-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/dwes-10-1-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
| 
26 Apr 2017
Review article |
| 26 Apr 2017
Review of applications for SIMDEUM, a stochastic drinking water demand model with a small temporal and spatial scale
Mirjam Blokker
CORRESPONDING AUTHOR
KWR Watercycle Research Institute, 3433 PE Nieuwegein, the
Netherlands
Claudia Agudelo-Vera
KWR Watercycle Research Institute, 3433 PE Nieuwegein, the
Netherlands
Andreas Moerman
KWR Watercycle Research Institute, 3433 PE Nieuwegein, the
Netherlands
Peter van Thienen
KWR Watercycle Research Institute, 3433 PE Nieuwegein, the
Netherlands
Ilse Pieterse-Quirijns
Amsterdam University of Applied Science, Faculty of Technology, Hogeschool van Amsterdam, Amsterdam, the Netherlands
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Cited
20 citations as recorded by crossref.
- Evaluation of harvesting urban water resources for sustainable water management: Case study in Filton Airfield, UK J. Kim et al. 10.1016/j.jenvman.2022.116049
- Water demand management at rural area using Micro-Component Analysis: a case study at Kenyir Lake, Malaysia N. Azlan et al. 10.1088/1755-1315/955/1/012027
- Assessing the Impact of Stochastic Demands and Fixture Purging on Free Chlorine Residuals in Premise Plumbing Systems E. Clements et al. 10.1021/acsestwater.3c00727
- Wide-scale study of 206 buildings in the Netherlands from 2011 to 2015 to determine the effect of drinking water management plans on the presence of Legionella spp. W. van der Lugt et al. 10.1016/j.watres.2019.06.043
- Methodology for estimating energy and water consumption patterns in university buildings: case study, Federal University of Roraima (UFRR) A. Almeida et al. 10.1016/j.heliyon.2021.e08642
- Machine Learning for Detecting Virus Infection Hotspots Via Wastewater‐Based Epidemiology: The Case of SARS‐CoV‐2 RNA C. Zehnder et al. 10.1029/2023GH000866
- Analytical Stochastic Microcomponent Modeling Approach to Assess Network Spatial Scale Effects in Water Supply Systems S. Díaz & J. González 10.1061/(ASCE)WR.1943-5452.0001237
- Smart Water Meters Can Save Lives during the COVID-19 Pandemic E. Salomons & M. Housh 10.1061/(ASCE)WR.1943-5452.0001548
- Relative Water Age in Premise Plumbing Systems Using an Agent-Based Modeling Framework J. Burkhardt et al. 10.1061/JWRMD5.WRENG-5888
- Impact of fixture purging on water age and excess water usage, considering stochastic water demands E. Clements et al. 10.1016/j.watres.2023.120643
- A review of household water demand management and consumption measurement H. Abu-Bakar et al. 10.1016/j.jclepro.2021.125872
- Characterizing stochastic water age in premise plumbing systems using conventional and advanced statistical tools E. Clements et al. 10.1039/D2EW00872F
- Drinking Water Temperature around the Globe: Understanding, Policies, Challenges and Opportunities C. Agudelo-Vera et al. 10.3390/w12041049
- Reduction in water consumption in premise plumbing systems: Impacts on lead concentration under different water qualities F. Hatam et al. 10.1016/j.scitotenv.2023.162975
- Decreasing the Discoloration Risk of Drinking Water Distribution Systems through Optimized Topological Changes and Optimal Flow Velocity Control E. Abraham et al. 10.1061/(ASCE)WR.1943-5452.0000878
- Systematic oversizing of service lines and water meters C. Douglas et al. 10.1002/aws2.1165
- Determination of Fixture-Use Probability for Peak Water Demand Design Using High-Level Water End-Use Statistics and Stochastic Simulation B. Josey & J. Gong 10.1061/JWRMD5.WRENG-6146
- Comparison of Bottom-Up and Top-Down Procedures for Water Demand Reconstruction D. Fiorillo et al. 10.3390/w12030922
- Leveraging Disparate Parcel-Level Data to Improve Classification and Analysis of Urban Nonresidential Water Demand B. Berhanu et al. 10.1061/(ASCE)WR.1943-5452.0001132
- Integrated Modelling to Support Analysis of COVID-19 Impacts on London's Water System and In-river Water Quality B. Dobson et al. 10.3389/frwa.2021.641462
20 citations as recorded by crossref.
- Evaluation of harvesting urban water resources for sustainable water management: Case study in Filton Airfield, UK J. Kim et al. 10.1016/j.jenvman.2022.116049
- Water demand management at rural area using Micro-Component Analysis: a case study at Kenyir Lake, Malaysia N. Azlan et al. 10.1088/1755-1315/955/1/012027
- Assessing the Impact of Stochastic Demands and Fixture Purging on Free Chlorine Residuals in Premise Plumbing Systems E. Clements et al. 10.1021/acsestwater.3c00727
- Wide-scale study of 206 buildings in the Netherlands from 2011 to 2015 to determine the effect of drinking water management plans on the presence of Legionella spp. W. van der Lugt et al. 10.1016/j.watres.2019.06.043
- Methodology for estimating energy and water consumption patterns in university buildings: case study, Federal University of Roraima (UFRR) A. Almeida et al. 10.1016/j.heliyon.2021.e08642
- Machine Learning for Detecting Virus Infection Hotspots Via Wastewater‐Based Epidemiology: The Case of SARS‐CoV‐2 RNA C. Zehnder et al. 10.1029/2023GH000866
- Analytical Stochastic Microcomponent Modeling Approach to Assess Network Spatial Scale Effects in Water Supply Systems S. Díaz & J. González 10.1061/(ASCE)WR.1943-5452.0001237
- Smart Water Meters Can Save Lives during the COVID-19 Pandemic E. Salomons & M. Housh 10.1061/(ASCE)WR.1943-5452.0001548
- Relative Water Age in Premise Plumbing Systems Using an Agent-Based Modeling Framework J. Burkhardt et al. 10.1061/JWRMD5.WRENG-5888
- Impact of fixture purging on water age and excess water usage, considering stochastic water demands E. Clements et al. 10.1016/j.watres.2023.120643
- A review of household water demand management and consumption measurement H. Abu-Bakar et al. 10.1016/j.jclepro.2021.125872
- Characterizing stochastic water age in premise plumbing systems using conventional and advanced statistical tools E. Clements et al. 10.1039/D2EW00872F
- Drinking Water Temperature around the Globe: Understanding, Policies, Challenges and Opportunities C. Agudelo-Vera et al. 10.3390/w12041049
- Reduction in water consumption in premise plumbing systems: Impacts on lead concentration under different water qualities F. Hatam et al. 10.1016/j.scitotenv.2023.162975
- Decreasing the Discoloration Risk of Drinking Water Distribution Systems through Optimized Topological Changes and Optimal Flow Velocity Control E. Abraham et al. 10.1061/(ASCE)WR.1943-5452.0000878
- Systematic oversizing of service lines and water meters C. Douglas et al. 10.1002/aws2.1165
- Determination of Fixture-Use Probability for Peak Water Demand Design Using High-Level Water End-Use Statistics and Stochastic Simulation B. Josey & J. Gong 10.1061/JWRMD5.WRENG-6146
- Comparison of Bottom-Up and Top-Down Procedures for Water Demand Reconstruction D. Fiorillo et al. 10.3390/w12030922
- Leveraging Disparate Parcel-Level Data to Improve Classification and Analysis of Urban Nonresidential Water Demand B. Berhanu et al. 10.1061/(ASCE)WR.1943-5452.0001132
- Integrated Modelling to Support Analysis of COVID-19 Impacts on London's Water System and In-river Water Quality B. Dobson et al. 10.3389/frwa.2021.641462
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Short summary
SIMDEUM, a tool to predict and explain drinking water demand over the day for a single household, has many applications from designing a water network to hydraulic and water quality modelling in the drinking water network. We give an overview of the applications and the relation between the type of application and the required model detail. The design requires a temporal scale of 1 s and a spatial scale of 20 homes or more; water quality modelling requires 5 min and a single home.
SIMDEUM, a tool to predict and explain drinking water demand over the day for a single...
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