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Potential Target Method #4 Using Density and ETo Factors. U4 Technical Subcommittee Meeting August 25, 2010. Tom Hawkins DWR. Tim Barr of Western Municipal Water District proposed a target method that uses variances in urban densities and ETo within a hydrologic region.
Potential Target Method #4Using Density and ETo Factors U4 Technical Subcommittee Meeting August 25, 2010 Tom Hawkins DWR
Tim Barr of Western Municipal Water District proposed a target method that uses variances in urban densities and ETo within a hydrologic region. • This presentation will be on the analysis performed with the purpose to determine if there is a relationship between these factors and water use.
The target setting equation for this method: Agency 2020 GPCD Target = [(HR Target – 55) X (Agency ETo/HR ETo) X (HR Urban Density/Agency Urban Density)] + 55
Primary factor affecting per capita water use is outdoor water use. • Outdoor water use can be affected by urban density (lower densities would have more irrigated landscape per person). • Outdoor water use can also be affected by weather (hotter/drier climates would have higher ET rates).
For this analysis, • Urban densities were developed using DWR population data and Dept of Conservation’s urban GIS data. • For weather, normal year annual ETo were used. Water use was DWR’s data from Calif Water Plan Update.
GIS layers used: • 2006 Urban Boundaries (From DOC Farmlands Mapping) • Normal Year Annual ETo (DWR and UC) • Detailed Analysis Units (DWR) • Tabular Data Used: • 2005 Urban Water Use by DAU (DWR) • 2005 Population by DAU (DWR)
Within ARCGIS, the three GIS layers, DAU, ETo, and Urban Boundaries, were all intersected to create a new layer. • From this new layer, a data table was created with this data by DAU: • Acreage of the urban area • Volume of annual normal year ETo for the urban area
Two more pieces of data were added to this data table: • 2005 Population by DAU • 2005 Urban water use by DAU • The urban densities by DAU were calculated: • Population / Urban acreage
I reviewed the DAU data for QA/QC. • I visually reviewed those DAU’s with high densities (higher than Orange DAU at 11.07 people/acre). It was apparent urban acreage were missing, either totally for some DAU’s, or only a portion of the urban areas were delineated within a DAU. Those DAU’s were removed. • It was also clear that DAU’s with low populations had unreasonably high or low densities (acreage or population problems) and removed DAU’s with a population of less than 5,000.
The data from the DAU data table were separated out by HR. • For each HR, the following data were used: • Population for each DAU, and for the HR • Urban acreage for each DAU, and for the HR • Urban water use for each DAU, and for the HR • ETo for each DAU, and for the HR
Urban densities by DAU and by HR were calculated: • Population/Urban acreage • The Density Factor was calculated: • HR urban density / DAU urban density • The ETo Factor was calculated: • DAU annual ETo/HR annual ETo • The final Density-ETo Factor was calculated: • Density Factor X ETo Factor
Urban per capita water use was calculated for each DAU using this equation: • DAU Volume of urban water use/DAU Population • A scatter chart was created for each HR using DAU per capita water use on the Y axis, and the DAU Density-Eto Factor on the X axis. • A regression trendline was added, along with the regression equation and R squared.
North Coast HR Density-ETo Factor
The results: • The data analysis did not result in a good regression relationship. • Does this disprove the concept? • Do not know • The datasets used may not be of high enough quality and coverage to be able to show a relationship.
ETo • Normal year was used, not 2005 data • The GIS layer used did not completely cover the whole coastline, where some urban acreage were not included in the analysis because of no ETo. • How accurate is the normal year ETo map? There was not a huge amount of data available in urban areas of the state when developed. • Is annual ETo the correct factor to use? Would the addition of effective precipitation improve the factor?
Water Use • The data used is based on voluntarily provided water use data by water agencies. • Not all provide data, some DAU’s probably are not represented by a water agency. • The data used for this analysis is all urban water use, including that supplied by water agencies and self supplied water (private wells).
Urban Area • DWR’s land use survey data a point-in-time dataset, and the urban areas would include data from the late 80’s. We don’t have digital surveys in much of the coastal urban areas. • DOC’s urban layer is missing some significant areas (Los Angeles County, San Francisco, and portions of other counties. • DOC’s data does show that in some areas, rural (low density) urban areas are delineated, and not in other areas. • The layer is for all urban, not just that in water agency boundaries.
Population • DWR has to develop population estimates by DAU. This is done using Census and DOF data and recent aerial imagery. Always room for improvement.
Implementing this proposal as a target method would require significant work to be able to come up with a supportable and agreeable urban delineation (acreage) by hydrologic region. • Should it be urban areas within water agency services areas? • Missing data, how would that be developed?