The aim of the data collection and model development was to understand the potential impacts of different seasonal pricing strategies on aggregate and metered domestic water demand. An early model representing domestic water pricing variables is shown in Figure 4.8.
Figure 4.8. Information requirements for domestic customer pricing decision
The model in Figure 4.8 shows how price elasticity for domestic water demand is strongly influenced by discretionary use, usually approximated as the difference between the summer and winter demand. This is the fraction of total demand that is generally expected to be responsive to a change in price. Price elasticity measures changes in the quantity demanded as associated with price changes for the good or service. The price elasticity of demand is a negative number. Based on price elasticity of -0.2, for example, a 10 percent increase in price is associated with a two percent decrease in usage.
Pricing can only be effective as a conservation tool if a meter is installed in the household. This is because a metered rate produces a water bill that varies with the amount of water used. Higher use results in a higher bill, and lower use results in a lower bill signalling in the mind of the consumer a need to be careful about their water use. This was the main driver for introducing universal household metering in Sofia in 1999 when the 25-year concession contract was agreed and International Water commenced management of Sofia’s municipal water supplies. As a result the water company estimates that around 98% of households in Sofia now have a meter installed.
4.3.1 Method
To examine discretionary demand (i.e. the difference between summer and winter use) in Sofia and the potential for using price as a conservation tool, monthly water demand data between 2000 and 2004 were supplied by the water company, Sofiyska Voda.
4.3.2 Results
The histogram in Figure 4.9, below, shows monthly water demand in Sofia for the years 2000 to 2004.
Figure 4.9. Monthly water supplied by Sofiyska Voda 2000-2004
A comparison between summer and winter months shows that discretionary demand is very low indicating that price will not be an effective conservation tool in the Sofia case. Consultation with members of the panel of informed practitioners revealed that there may be a number of reasons for this. One reason cited was that many people in the suburbs access water for irrigation and livestock watering from their own boreholes. This water is not metered and would not be affected by any price increase. A second reason cited was that most people in the city (around 60%) live in multi-family housing blocks and do not have gardens.
These findings are interesting from a cultural perspective because in most western developed world cases, i.e. in the USA, Australia, UK and Germany, discretionary demand accounts for between 15-50% of summer demand, making price mechanisms an effective short-term measure for controlling demand, especially during a dry summer.
Although it is possible that, in future, changes might occur that will result in higher discretionary demand in Sofia, e.g. increased affluence, charging for groundwater, larger gardens and an increase in outdoor water use etc, the present very low
0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 30,000,000
January February March April May June July August September October November December
Cubicmeters
2000 2001 2002 2003 2004 Limits 2004
Data source: Sofiyska Voda, 2007
discretionary demand means seasonal pricing will have a negligible impact on domestic water demand.
4.3.2.1 Impacts of price and WDM measures on Sofiyska Voda revenues
When considering impacts of demand management options on water company revenues, only a reduction in metered water demand is relevant. Therefore, in order to model the impacts of price and other WDM measures on total water demand as well as on the water company’s revenues it was necessary to disaggregate the metered component of domestic water demand from the total demand. It was also necessary to first consider the impacts of WDM programmes in terms of their impact on different components of water demand, and only then could they be combined to develop the conditional probability table representing their impacts (i.e. water savings) on total demand.
Figure 4.10, below, shows the disaggregated demand components used by Sofiyska Voda for operational purposes which were helpful in understanding how different WDM options impact on domestic demand.
Figure 4.10. Components of Sofia’s domestic water supply
Using the above information the Influence diagram structure for impacts of domestic water price and disaggregated demand was developed as shown in Figure 4.11. Low discretionary demand is represented by the conditional probability tables: p(domestic water demand | domestic water price) and p(metered water demand | domestic water price. Impacts of different WDM programmes on disaggregated demand are
Leakage
Municipal uses (government offices, universities, public spaces etc)
Service industry (hotels, restaurants, sports facilities etc)
Other industrial uses (other businesses)
represented by the the conditional probability tables: p(domestic water demand | WDM programme water savings | WDM programme options).
Figure 4.11. Influence diagram structure for impacts of domestic water price on total domestic demand and WDM programmes and water price on metered demand.
The following subsection describes how the data collected during the knowledge elicitation were used to develop conditional probabilities to forecast the water saving potential of different WDM programmes.