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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.

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Potential Target Method #4 Using Density and ETo Factors

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Potential target method 4 using density and eto factors l.jpg

Potential Target Method #4Using Density and ETo Factors

U4 Technical Subcommittee Meeting

August 25, 2010

Tom Hawkins


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  • 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.

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  • The target setting equation for this method:

    Agency 2020 GPCD Target


    [(HR Target – 55)


    (Agency ETo/HR ETo)


    (HR Urban Density/Agency Urban Density)]



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  • 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).

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  • 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.

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  • 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)

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10 Hydrologic Regions

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Detailed Analysis Units

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Urban Areas (DOC)

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Normal Year ETo Zones

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  • 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

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  • 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

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  • 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.

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  • 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

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  • 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

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  • 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.

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North Coast HR

Density-ETo Factor

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San Francisco Bay HR

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Central Coast HR

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South Coast HR

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Sacramento River HR

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San Joaquin River HR

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Tulare Lake HR

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South Lahontan HR

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Colorado River HR

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NC, SFB, CC, and SC HR’s

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NC, SFB, CC, and SC HR’s (over 40,000 pop)

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SR, SJR, and TL HR’s

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SR, SJR, and TL HR’s (over 40,000 pop)

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  • 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.

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  • 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?

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  • 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).

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  • 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.

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  • 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.

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  • 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?

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  • Questions/Comments?

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