Survey of Data Related to Municipal Water Systems in Utah

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Presentation transcript:

Survey of Data Related to Municipal Water Systems in Utah Paul Harms CEE 6440: GIS in Water Resources Utah State University Fall 2002

Relating ancillary data to water use data: May help explain why water systems use different amounts of water. May improve estimates of existing water demands. May allow categorization for better use of random sampling. May improve predictions of future water demands, using projections of the related data.

Correlations with residential water use: IWR-MAIN Household income Persons per household Housing density Average maximum temperature Rainfall Price of water Wasatch Front Model Persons per household Lot size Assessed value Soil type Season Dual system

Town Size: Total GPCPD Domestic GPCPD Total Use number mean stan.dev. Total GPCPD Domestic GPCPD Total Use number mean stan.dev. coef. var. Population (ac-ft/yr) small 38 289.13 133.58 0.46 235.86 126.58 0.54 64660 21180 mid 9 275.49 114.67 0.42 191.44 76.34 0.40 114863 38533 metro 13 188.21 81.74 0.43 131.68 47.69 0.36 748129 181726 total 60 265.22 0.48 206.62 114.56 0.55 927652 241438

Domestic Fraction: Dual Fraction: r n sig.? GPCPD/Domestic Fraction Correlation Coef. = 0.0207 60 no Metro GPCPD/Domestic Fraction Correlation Coef. = -0.7912 13 yes Dual Fraction: GPCPD/Dual Fraction Correlation Coef. = -0.4444 Metro GPCPD/Dual Fraction Correlation Coef. = -0.9004

>90% Surface Water Source: Well Fraction: r n sig.? GPCPD/Well Fraction Correlation Coef. = -0.0816 60 no Metro GPCPD/Well Fraction Correlation Coef. = 0.4122 13 >90% Surface Water Source: Average GPCPD # yes: 4 169.70 # no: 56 272.04

Average Maximum Temperature: Latitude: r n sig.? GPCPD/Latitude Correlation Coef. = -0.0817 60 no Average Maximum Temperature: GPCPD/Temperature Correlation Coef. = -0.0145 Metro GPCPD/Temperature Correlation Coef. = 0.5516 13

Average Annual Precipitation: sig.? GPCPD/Ann. Precip. Correlation Coef. = -0.0319 60 no Metro GPCPD/Ann. Precip. Correlation Coef. = -0.6297 13 yes Average JJAS Precipitation: GPCPD/JJAS Precip. Correlation Coef. = 0.0367 Metro GPCPD/JJAS Precip. Correlation Coef. = -0.4400

Water pricing structures Flat charge Uniform rate Increasing block rate Decreasing block rate

Example: Escalante Culinary Water Unchanging $17 for the first 15,000 gallons used each month. $1.50 per 1000 gallons for the next 15,000 gallons. $2 per 1000 gallons after 30,000 gallons.

Rate Structure: # no data: 18 # flat charge: Average GPCPD Average GPCPD # uniform rate: 25 uniform 275.31 # increasing block: 15 increasing 287.86 # decreasing block: 2 decreasing 297.56 # metro uniform: 6 metro uniform 230.09 # metro increasing: 3 metro increasing 90.01

Linear Regression Metro GPCPD = 248.966 – 161.851*(dual fraction). se = 36.2095. R2adj = 0.80374. Metro Total Use = -17359.8 + 0.278205*(pop) – 1516.78*(dual) + 417.821*(temp) + 214.045*(annPrecip) – 3574.23*(sumPrecip). se = 1916.91. R2adj = 0.99342.

Problems Obtaining trustworthy data Sample not random Different data types sometimes cover different years Some correlations may exist but be obscured by stronger correlations

Conclusions Correlations significantly different from zero: more population – more total use more dual – less GPCPD more metro annual precipitation – less GPCPD lower metro domestic fraction – more GPCPD

Conclusions Other trends: smaller water system – more variable GPCPD higher latitude – less GPCPD higher metro and mid temperature – more GPCPD more metro summer precipitation – less GPCPD metro increasing block rates – less GPCPD higher base rate limit – less GPCPD (counter-intuitive) higher rate per 1000 gallons – less GPCPD more surface water dependent – less GPCPD

Conclusions Grouping by town size appeared appropriate, and may be useful for random sampling. Large water systems appeared predictable. Small water systems appeared unpredictable. Averages over many small systems may be useful. Estimating or predicting water use at individual small systems with this ancillary data would not be valid.