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Survey of Data Related to Municipal Water Systems in Utah

This survey explores correlations between ancillary data and water use in Utah, aiding in predicting and improving future water demands. It examines factors like household income, pricing structures, and climatic conditions to offer insights into varying water usage. Conclusions drawn highlight the impact of population density, climate, and pricing strategies on water consumption patterns across different types of municipalities. Grouping by town size is suggested for efficient sampling and predicting water usage trends.

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Survey of Data Related to Municipal Water Systems in Utah

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

  2. Relating ancillary data towater 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.

  3. 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 Correlations withresidential water use:

  4. Water pricing structures • Flat charge • Uniform rate • Increasing block rate • Decreasing block rate

  5. 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.

  6. 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.

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

  8. 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

  9. 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

  10. 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.

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