(269c) Assessing Domestic Water Consumption Spatial Distribution In An Urban Setting

As climate change continues to wreak havoc upon our planet, the availability of water resources has become erratic in some regions of the World. A study in 2007 found that water consumption is positively related to climate change. The study discovered that for every 1°C temperature increase in mean annual temperature there is a 60.76L increase in the amount of water per dwelling (Balling and Gober 2007). Therefore, as the temperature in cities increases, so does water consumption. An increase in precipitation has the opposite effect on water consumption. Balling and Gober (2007) also found a reduction (increase) in annual precipitation of 10mm would increase (decrease) water use by 4 liters per capita per day according to data taken in Phoenix, Arizona.

Research has already begun as to how to conserve water resources. The United States Environmental Protection Agency (EPA) has developed a Water Resource Adaptation Program (WRAP). The aim of the program is to provide water resource managers and decision makers with the tools they need to adapt water resources to future climate change and demographic and economic development (United States Environmental Protection Agency 2009). One aspect of the WRAP research is to understand the demand for water and energy under various urban development scenarios. The intent of this research is to provide means to support three of the five EPA WRAP goals: clean air and global climate change, clean and safe water, and compliance and environmental stewardship (United States Environmental Protection Agency 2009).

This paper presents a study developing a water consumption system (Water-SB-PSS) to establish the connections between domestic water consumption and future development alternatives in the context of climate change and residents’ life style. The Water-SB-PSS enables its users to relay water conservation to water consumption rates, land use configuration, and climate change (precipitation or temperature). Results display water consumption for each scenario using maps, graphs, and tables. Differences between scenarios also can be compared.  

Scenarios can be used to “discover unknown or poorly understood interrelationships” (Hopkins and Zapata 2007). The scenario-based process works by creating a set of plausible alternatives and uses them to illustrate possible outcomes of various decisions. Scenarios need to reflect a story, explaining how life could feasibly be lived, demanding that each possible scenario be analyzed objectively (Avin and Dembner 2001). Questions can be answered such as “What do you think might happen if all residents of a city reduced their indoor water consumptions by installing low flow toilets and other technologies in their household?”

The Water-SB-PSS is implemented with a commercial planning support system software package – CommunityViz (Placeways). CommunityViz can be used to make quicker, increasingly informed decisions about various issues and can also be used to engage and inform the public (The Orton Family Foundation 2004). This analysis engine basically helps to reveal possibilities and opportunities visually (Sipes 2003).  

The Water-SB-PSS is made up of four components: user input, database, simulation models, and output. The input of the system consists of three components. The Change of life style component consists of how people live their life in light of climate change. In terms of water consumption, it may be reflected in modifying turf, using water conservation showering heads etc. Future land use and/or infrastructure plans are represented by spatial data layers such as land use plan map or water distribution network. A user may modify those data layers to analyze the impact of different development plans.  The SB-PSS database contains both spatial and non-spatial data, which represent user input, city characteristics, and modeling output. The simulation model component consists of various simulation or optimization models which computing corresponding changes from adjustment of input. the models to be included in this Water-SB-PSS would be traffic, drinking water, waste water, storm water, air quality (black carbon and PAH), and climate model (precipitation and temperature). The simulation results are saved into the database for the output component to retrieve and present to the Water-SB-PSS users.

Urban domestic water consumptions consist of three types - indoor consumption, turf consumption, and pool consumption for each parcel. The Water-SB-PSS user adjusts the inputs of the consumption rates to represent scenarios of different human behavior. The parcel data layer contains population, household, employee, and land use data. The user adjustment of those data values makes it possible to reflect different development scenarios. The climate change input variables provide a way of including climate change impact in the scenario analysis. The parcel level water consumption can then be summarized by land use types, or by different summary areas. The results can be then analyzed for a scenario or multiple scenarios can be compared.

Before a more robust climate change model is developed we constructed a set of linear regression models to predict water consumption based on ambient temperature and precipitation. Previous research has shown that there is a positive correlation between temperature and water consumption. When there is increased precipitation people use less water (Balling and Gober 2007). Such regression models must be specific to the study site.

A user may adjust input variables to represent different scenarios. Since the model considers three types – turf, swimming pool, and indoor water consumptions, the input variables are grouped accordingly. Input variables are treated in three ways in CommunityViz –modification of the geometry of a data layer, change of attributes of a data layer, or usage of assumptions. Four land use based indoor water consumption assumptions are developed, which represent per capita daily water usage for single family, multi-family and mixed use, resort and casino guests, and commercial, industrial, resort and casino, and golf course employees. Two assumptions are developed for pool water consumption – the annual water loss via evaporation measured as gallons per square feet of pool surface and the average depth of swimming pools in feet. Monthly water consumption assumptions are developed for turf water usage from April till September.

Dynamic attributes are created for parcels, census block groups, and neighborhoods. At the parcel level, daily indoor water consumption is first calculated and then aggregated into monthly total and annual total. Pool consumption is an annual attribute but is only considered for months April through September, as those months are when pools are typically filled. Turf water consumption is first calculated by month and then added to get the annual values. The monthly consumptions are only calculated for April through September since those are the months when lawns are more frequently watered aside from precipitation. Annual turf consumption is the sum of the April through September turf consumptions.

Scenarios are developed in three ways – 1) change of water consumption rates. The indoor water consumption depends on the number of people who uses water and how they use water. In special cases, such as hotels, resorts and casino, the number of guests also affect indoor water consumption. 2) change of population, employees, and land use. Modification of corresponding attributes of the parcel data layer may represent such change. Water conservation rates are represented by land use. A user may also edit the pool or turf data layer to reflect the number of pools and the sizes of pools and turf by parcel. 3) climate change. A user can change for a particular scenario by including climate change variables – temperature and precipitation. Indicators and graphs are used to present water consumption results. They include annual water consumption by land use, by neighborhood, and by type for the entire site.

This research extends the EPA's research in water availability by using the GIS planning software CommunityViz to create scenarios based on water consumption characteristics per land use. The model was created as a way to gauge different scenarios of water resources in the future. It can help encourage community participation, negotiation, and consensus building of multi-interest stakeholders to conserve water, whether it is through changes in development directives, water resource adaptation engineering or policy enactment. Better planning of water resources can help to develop more sustainable communities in a time when sustainability is increasingly needed. The phrase “think globally, act locally” is as far as we go at the moment with changing the habits of people to help our environment. This research can take the phrase a step further to “think globally, act locally, start with me!” It can give each individual community member the information they need to change in their water consumption habits.

Water consumption can determine the need for potable water pipes. Increased vacancies will decrease the rate at which water is used in the potable water pipes. This can affect water quality as well. Additionally, water consumption is linked to wastewater. By understanding the amount of water that will be used in the area, the amount of water that will flow into the wastewater system may be able to be predicted. This could even predict where the system needs to be expanded or modified due to vacancies.       

Acknowledgement

The project is sponsored by U.S. Environmental Protection Agency contract no. EP-C-05-056 work assignment no. 4-84