Introduction
A water use node represents urban water demand and water consumption behaviour. Urban Developer offers two methods for simulating water use behaviour:
- Average daily model (the Average Water Use node)
- Behavioural model (the Behavioural Water Use node)
The behavioural model provides simulation of water use using the Behavioural End-use Stochastic Simulator (BESS) of Thyer et al. (2011). BESS stochastically simulates individual end-uses (outdoor, shower, washing machine, toilet, tap etc) at the household scale at sub-daily time steps using algorithms that probabilistically simulate an individual household’s use of common household water-using appliances. The conceptual framework for BESS is provided as follows:
Figure 1. BESS conceptual framework.
, described further in the Urban Developer Plugin SRG.
For indoor water uses, the water use simulations for each household are based on the type of water-using appliance (end-use) and the household occupancy of that household. The difference from the average daily model applied in the Average Water Use node is that instead of specifying an average daily volume and percentages for each end-use, the user specifies the water-using appliance and household occupancy and BESS simulates the water for each individual end-use using the in-built parameters for the water use event dynamics. The types of water-using appliances for each end-use currently supported are listed in options for indoor water use appliance types. This enables users to simulate the effects of changes in the uptake of water efficient appliances.
The appliances and occupancy for each household can be specified in several different ways:
- Fixed occupancy and appliances – where the type of appliances and occupancy for each house are fixed by the user
- Sampled appliances and occupancy – where the users inputs probability distributions for the occupancy and water-using appliance. At the start of Urban Developer run the occupancy and appliance type is randomly sampled for each house in the Behavioural Water Use nodes.
- Average appliances and occupancy – calculates the mean for the end-use instead of calculating the demand per minute (based on events) for each end use, as in the fixed and sampled occupancy methods. These values can simply multiplied for each house (as they will all have the same average).
Further details on these configurations are given in Behavioural Model Configuration.
The statistical distributions used by BESS to generate the sub-daily indoor water use are based on the end-use study of Roberts et al. (2005). Users are encouraged to check that the predicted water use statistics provided by BESS match their expectations.
BESS uses a
By default, BESS uses a sub-daily diurnal pattern based on Roberts et al. (2005) to vary the probability of water use events occurring throughout the day. Future versions of Urban Developer will enable users to input their own diurnal pattern.
For outdoor water use, the behavioural model uses a time series or monthly varying pattern of average daily values, which can be input by the user - similar to the average daily model. For the sub-daily outdoor water use, the daily values are evenly distributed throughout the day. Future versions of the behavioural model may incorporate the behavioural impact daily weather has on outdoor water use variability (Micevski et al., 2011)
The Behavioural Water Use node allows the user to specify a unique combination of end-uses which will be applied to one or more houses. In this way the node can become a template representing a specific urban demand configuration. For example, a single node can be configured to represent all Detached homes with a Pool.
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There are restrictions on which node inputs and outputs you can connect together. See Urban Developer node connection rules.
The Behavioural Water Use node is available for Urban Scenarios only.
Node Dependencies
Node Dependencies
The Behavioural Water Use node requires that the following inputs are configured through the Urban Developer Options:
- Climate inputs
- Diurnal pattern
- Appliance types
- Sampled Appliances & Occupancy (optional, required for the behavioural model with sampled appliances and occupancy only)
The Behavioural Model Configuration describes how these inputs are utilised by the behavioural model.
Node Outputs
Connect to any other end-use stream. For example, you can track your garden irrigation through this end-use, and link it back to a pervious area node in your model to capture the effects of run-off of irrigating your pervious area.
allocation and application of these parameters is further described in the Urban Settings section in the Urban Developer Plugin User Guide and the Behavioural Model Configuration section in the Urban Developer Plugin SRG.
Restrictions
There are restrictions on which node inputs and outputs you can connect together. See Urban Developer node connection rules.
The Behavioural Water Use node is available for Urban Scenarios only.
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| Node Property | Notes | ||||||
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| Number of houses | Specify the number of houses the node representsrepresents | ||||||
| Occupants per house | Specify the number of occupants per household (applies only when the behavioural model configuration is set to | fixed appliances and occupancy.Appliances. When the behavioural model configuration is set to | sampledSampled appliances and occupancy, these properties are | not usedgrayed out in the user interface. Refer to | Behavioural Model Configuration forsection 2. Urban Settings for details. | Occupants per household | Specify the number of occupants per household) |
| Average appliance demand | Switches between a Stochastic (BESS) and Average method of demand generation Stochastic demand generation will use random number generators to see if water use events occur throughout the day, based on the hourly likelihood for the particular end use. Some end use items also have a random generator for the volume of water used and / or the length of the event. Average demand generation will calculate the average event likelihood and demand volume for a timestep. This means each end use will generate the same demand rate for all timesteps until parameters change to affect end use item rating being used, number of people in the house, or number of houses being modelled. Outdoor use is the exception to this rule as it uses a specified data source, function, or monthly pattern for this demand generation. | ||||||
| End-use appliance type | For Indoor end-use , specify the appliance type (e.g. type of shower, dishwasher, toilet, etc). See includes showers, taps and dishwashers, toilet and dishwashers as appliance types. Specifications for indoor water use appliance types in Behavioural model with fixed appliances and occupancy.It is currently not possible to specify an appliance type for the are set under the Urban Developer Options described in section 2. Urban Settings. Pool is currently the only end-use available under Outdoor end-use. | ||||||
| Outdoor average daily demandSpecify | the The average daily outdoor demand can be specified using a single value, a time series, a function or a monthly pattern or a time series. By default a monthly pattern is applied. | ||||||
| Supply source priorities | For each indoor/outdoor end-use, specify which supply sources are available an order of preference. For example, for the end-use Toilet (illustrated in Figure 2):
Un-checking Use for a supply source specifies that it will not supply that particular end-use, in order of preference. | ||||||
| Discharge breakdown | For each indoor/outdoor end-use, specify the percentage of water discharged as blackwater, greywater, or Irrigation/other wastewater. The values will be rescaled so that they sum to 100%. |
User Interface
The Behavioural Water Use node is configured via the node Feature Editor, illustrated below in Figure 1. to Figure
24. The first window of the Behavioural Water Use node
editor.
Temporal Variability in Indoor Water Use Events
Individual end-use events are generated in a two stage process. The first stage determines whether a given water use starts in a particular time step, and is based on the probability of occurrence, for a particular end-use. The second stage tracks the subsequent behaviour of that water use over the following time steps, and is dependent on the end-use event volume and water usage pattern.
In general the probability of occurrence for each event was a function of the frequency of events per person per day, the household size and a diurnal factor. The diurnal factor converts the frequency of events per day into the probability of an event occurrence in a given minute taking into account the diurnal variation of the event, which is an input. The water use event volume and the water usage pattern is dependent on the type of water use event and the appliance type. In general, the end-use event volume is sampled from a probability distribution, and the water usage pattern is applied to this volume to produce a water use time series. Refer to Thyer et al. (2009) and references cited therein for details.
Fixed appliances and occupancy
The behavioural water use model configuration with fixed appliances and occupancy allows you to set appliance types for each end use (showers, washing machines, and toilets), household occupancy and outdoor use for each water use node.
Using the behavioural model with fixed appliances and occupancy is the recommended approach when you are simulating a smaller number of houses (< 400), and you want to specify exactly the type of appliances and occupancy for each house.
Similarly to the average daily model, you select the supply source preference for each individual end use.
For this behavioural model configuration (fixed appliances and occupancy) you set the indoor end-use appliance types and occupancy for each water use node. Refer to the Node Properties for details.
Sampled appliances and occupancy
The behavioural water use model configuration with sampled appliances and occupancy allows you to specify random sampling of occupancy and appliance types, for each household, from statistical distributions.
Using the behavioural model with sampled appliances and occupancy is only recommended when you are simulating a larger number of households (> 400) and you do not want to set the appliance types /occupancy for each house.
Sample size requirements
If you specify sampled appliances and occupancy, you must specify a minimum number of houses in order to provide a statistically-reliable sample of the household occupancy and appliance type.
Due to random sampling in any particular Urban Developer run, the percentage of houses actually sampled for each household occupancy and appliance type (the sampled percentage) will not be exactly the same as what you specify (the true percentage).
For example - if you specify only 10 houses, with a true probability of 0.2 for 3-Star showers and 0.8 for 1-Star showers, the chance of the sampled percentage being very different (eg: 0.5 3-Star and 0.5 2-Star) is much greater than with a large sample size.
The recommended minimum number of 400 houses ensures that for true percentages greater than 10%, the sampled percentage of houses is within 30% of the true percentage for 90% of the time.
You can specify a number of houses smaller than 400, but should be aware that the sampled percentage of household occupancy and appliances types may be different than the percentage you originally specified.
Random Seed
Random seeding provides a way to control randomisation of simulation outcomes. Random seeding applies to both sampled, and fixed, appliances configurations. The seed applies to both allocation of appliance types (eg Shower 0-Star or Shower 3-Star) to a house, and the actual water use, given the specified appliances. You can obtain repeatable results, or varied results, or repeatably-varied results with the random seed settings.
When using probabilistic simulations in models such as BESS, it can be difficult to reproduce results due to the random generation of water use.
The random seed is currently not editable in the Urban Developer Plugin, but this feature is planned for future versions to allow repeatable results with sampled appliances and occupancy.
Diurnal Pattern
The statistical distributions used by BESS to generate the sub-daily indoor water use are based on the end-use study of Roberts et al. (2005). Users are encouraged to check that the predicted water use statistics provided by BESS match their expectations. BESS uses a diurnal variation to vary the probability of water use events occurring throughout the day. It disaggregates the daily demand data to a sub-daily time-step using a non-dimensionalised diurnal pattern.
Sampled Behavioural
Spatial Variability
The household size and the type of water using appliances vary from household to household. To capture this spatial variability the household size and appliance type for each type of water use event is randomly sampled for each household from a probability distribution based on the proportion of household sizes/appliance types. An example of these probability distributions based on Roberts [2005] is provided below. This information can also be obtained from Australian Bureau of Statistics (ABS) surveys
The Behavioural End-use Stochastic simulator (BESS) stochastically simulates individual end-uses (outdoor, shower, washing machine, toilet, tap etc) at the household scale at sub-daily time steps. The indoor component simulates differences in household size, uptake rates of water efficient appliances and diurnal variation in end-uses. The behavioural water use model configuration with sampled appliances and occupancy allows you to specify random sampling of occupancy and appliance types, for each household, from statistical distributions.
Using the behavioural model with sampled appliances and occupancy is only recommended when you are simulating a larger number of households (> 400) and you do not want to set the appliance types /occupancy for each house.
Menu item Notes Fixed appliances and occupancy This option produces a repeatable, probabilistic simulation of water use, using fixed (ie user-specified) appliances and occupancy rates for each water use node. Sampled appliances and occupancy This option produces a repeatable (if configured in Random Seed Settings, see below), probabilistic simulation of water use, using sampled appliances and occupancy from user-defined probability distributions. Random Seed Settings This option allows you to set the random seed used by the BESS model for water use simulation - this enables production of repeatable random series. See Water Use node (page 143) for more information.
References
Micevski, T., Thyer, M., Kuczera, G. (2011) A Behavioural Approach for Household Outdoor Water Use Modelling. Paper submitted to Water Resources Research (April 2011).(Figure 1) allows the user to set the Number of houses which will use the end-use configuration specified on this node. This will be 1 if applying the node as a template for an Urban Combination Configuration run. Water end-use is categorised as Indoor and Outdoor use.
The average appliance demand is an option that can be used in conjunction with sampled or fixed appliances and occupancy.
Average values for usage frequency and water consumption are used, rather than simulating the water consumption for individual appliance usage events by sampling from the probability distributions set up under the Urban Developer Options described in section 2. Urban Settings. The average values are configured in the Appliances menu.
The average appliance demand model is enabled using the Use Average Demand check box in the Behavioural Water Use node Feature Editor.
Figure 1. Behavioural Water Use node editor
Indoor demand
Four end-use options are available for Indoor water demand allocation (Figure 2). Each end-use is defined by an end-use Rating (according to specification configured in the Urban Settings interface of the Urban Developer Options), a Supply type and a Discharge type.
Supply occurs according to the priority allocated to a particular Supply type. For example, for the end-use Toilet (illustrated in Figure 2) rainwater is the first preference for toilet flushing and, if no rainwater is available, then Mains water is used as the second preference for flushing. Un-checking Use for a supply source specifies that it will not supply that particular end-use. Two unspecified Alternate Supply options are available to represent supply from a source other that Mains or Rainwater, such as greywater.
Discharge can got to blackwater, greywater or an irrigation/other option. Discharge to each option is allocated as a part of the total discharge and the values will be re-scaled so that they sum to 100%.
Figure 2. Configuring Indoor end-use options in the Behavioural Water Use node editor
Outdoor demand
Outdoor demand typically replicates a seasonal variation in water use (e.g. domestic garden use which is higher during dryer months) and can therefore be modelled using a Time series, a Function or a Monthly pattern (Figure 3). Outdoor demand is also more likely to be impacted by long-term variations in climate.
As with the Indoor end-uses, a Supply type and a Discharge type are available for Outdoor demands. A Pool (Figure 4) can be added and can have different Supply and Discharge types to the general Outdoor demand.
Figure 3. Configuring Outdoor demand options in the Behavioural Water Use node editor
Figure 4. Configuring Outdoor demand options in the Behavioural Water Use node editor
References
Roberts, P. (2005) 2004 Residential End Use Measurement Study, Final Report: Yarra Valley Water, Victoria.Thyer, M. A., Duncan, H., Coombes, P., Kuczera, G., & Micevski, T. (2009) A probabilistic behavioural approach for the dynamic modelling of indoor household water use. In H2009: 32nd Hydrology and Water Resources Symposium: Adapting to Change, 30 November - 3 December 2009, Newcastle, Australia (p. 1059).
Thyer, M., Micevski, T., Kuczera, G., and Coombes, P. (2011) A Behavioural Approach to Stochastic End Use Modelling. Paper presented at Oz Water, 9-11 May 2011, Adelaide.
Acknowledgements
This material has been adapted from:
eWater Cooperative Research Centre (2011) Urban Developer User Guide: Urban Developer v1.0.0, eWater Cooperative Research Centre, Canberra, 29 June 2011. ISBN 978-1-921543-40-1