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| Type: | Resource | |
| Storage: | The size of this resource is 1.7 MB | |
| Created: | Jan 19, 2021 at 11:58 p.m. | |
| Last updated: | Jun 16, 2021 at 4:14 p.m. (Metadata update) | |
| Published date: | Jan 20, 2021 at 12:42 a.m. | |
| DOI: | 10.4211/hs.e9137bf4054a45778a7944d3ebceea0f | |
| Citation: | See how to cite this resource | |
| Content types: | Model Program Content |
| Sharing Status: | Published |
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| Views: | 2222 |
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Abstract
Urban water demand modeling with regression identifies explanatory factors of water use in cities. A generalized demand modeling approach was developed for over 400 urban water supply agencies in California. Using standardized data from self-reported sources for agencies across the state, a batch-processing approach was used to create standardized urban water demand models. The models were developed to test the validity of a simplified and generalized demand modeling approach using monthly available data. Semilog, multivariate regression models were developed for each urban water supply agency. Consumption from residential (single- and multi-family), commercial, industrial, and institutional water use were considered as outcome variables. Explanatory variables include indicator variables for months in a calendar year, periods of water conservation requirements during a 2011-16 severe drought, population, and water rates. The models were of reasonable fit, with adjusted R-squared values ranging from 0.6-0.99. Visual inspection revealed that the monthly models captured trends with reasonable accuracy. The time frame for models was 2013-18, a period with standardized available data through statewide reporting. The modeling approach has been subsequently further extended to incorporate additional climate variables (precipitation and evapotranspiration) for sector-specific models. The models are intended to understand explanatory factors of demand through a generalized modeling approach and not intended to be used for water supply operations without further refinement and testing. The approach can be adapted to many types of cities.
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| MIGRATED_FROM | Model Program Resource |
Related Resources
| The content of this resource is derived from | California State Water Resources Control Board: Electronic Annual Reports (partial) |
| This resource has been replaced by a newer version | Porse, E. (2021). Urban Water Demand Regression Modeling for California Water Suppliers, HydroShare, https://doi.org/10.4211/hs.f70cefe684b746c6b37dd4ca056a6b34 |
How to Cite
This resource is shared under the Creative Commons Attribution-NoCommercial CC BY-NC.
http://creativecommons.org/licenses/by-nc/4.0/
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